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BigFraction.
AbstractUnivariateDifferentiableSolverFieldMatrix methods regardless of the underlying storage.FractionFormat and BigFractionFormat.AbstractIntegerDistribution.AbstractIntegerDistribution(RandomGenerator) instead.
SimpleValueChecker.SimpleValueChecker()
RandomGenerator interface.AbstractRealDistribution.AbstractRealDistribution(RandomGenerator) instead.
SimpleValueChecker.SimpleValueChecker()
StorelessUnivariateStatistic interface.SubHyperplane.UnivariateStatistic interface.Adams-Bashforth and
Adams-Moulton integrators.FunctionUtils.add(UnivariateDifferentiableFunction...)
Complex whose value is
(this + addend).
Complex whose value is (this + addend),
with addend interpreted as a real number.
BigInteger,
returning the result in reduced form.
this and m.
m to this matrix.
this and m.
this and v.
this and v.
v.
this and m.
this and m.
m.
this and m.
this and v.
m.
v.
this and m.
v.
this and v.
Collection of chromosomes to this Population.
data.
ResizableDoubleArray.ExpansionMode.ADDITIVE instead.
this matrix.
this matrix.
this matrix.
this matrix.
this matrix.
this matrix.
SummaryStatistics from several data sets or
data set partitions.(bracketed univariate real) root-finding algorithm may accept as solutions.double[]
arrays.
double[]
arrays.
SummaryStatistics.
Math.FieldElement[][] array to store entries.FieldMatrix<T> with the supplied row and column dimensions.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using v as the
data for the unique column of the created matrix.
FieldMatrix<T> using v as the
data for the unique column of the created matrix.
RealMatrix using a double[][] array to
store entries.RealMatrix using the input array as the underlying
data array.
v as the
data for the unique column of the created matrix.
FieldVector interface with a FieldElement array.ArrayFieldVector.ArrayFieldVector(FieldVector, FieldVector)
ArrayFieldVector.ArrayFieldVector(FieldVector, FieldElement[])
ArrayFieldVector.ArrayFieldVector(FieldElement[], FieldVector)
RealVector interface with a double array.SimpleValueChecker.SimpleValueChecker()
SimpleValueChecker.SimpleValueChecker()
SimpleVectorValueChecker.SimpleVectorValueChecker()
BigDecimal.
BigDecimal following the passed
rounding mode.
BigDecimal following the passed scale
and rounding mode.
BigFraction equivalent to the passed BigInteger, ie
"num / 1".
BigFraction given the numerator and denominator as
BigInteger.
BigFraction equivalent to the passed int, ie
"num / 1".
BigFraction given the numerator and denominator as simple
int.
BigFraction equivalent to the passed long, ie "num / 1".
BigFraction given the numerator and denominator as simple
long.
FieldMatrix/BigFraction matrix to a RealMatrix.
BinaryChromosomes.n choose k", the number of
k-element subsets that can be selected from an
n-element set.
double representation of the Binomial
Coefficient, "n choose k", the number of
k-element subsets that can be selected from an
n-element set.
log of the Binomial
Coefficient, "n choose k", the number of
k-element subsets that can be selected from an
n-element set.
lowerBound <= a < initial < b <= upperBound
f(a) * f(b) < 0
If f is continuous on [a,b], this means that a
and b bracket a root of f.
lowerBound <= a < initial < b <= upperBound
f(a) * f(b) <= 0
If f is continuous on [a,b], this means that a
and b bracket a root of f.
(univariate real) root-finding
algorithms that maintain a bracketed solution.100, 50 (see the
other constructor).
100, 50 (see the
other constructor).
(lo, hi), this class
finds an approximation x to the point at which the function
attains its minimum.BSP tree nodes.MathArrays.buildArray(Field, int, int)
MathArrays.buildArray(Field, int)
byte.
sum of squared residuals,
SSTO is the total sum of squares, n is the number
of observations and p is the number of parameters estimated (including the intercept).
WeibullDistribution.getNumericalMean()
ZipfDistribution.getNumericalMean().
FDistribution.getNumericalVariance()
HypergeometricDistribution.getNumericalVariance().
WeibullDistribution.getNumericalVariance()
ZipfDistribution.getNumericalVariance().
sum of squared residuals
and SSTO is the total sum of squares
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above).
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above).
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above).
ceil function.ResizableDoubleArray.checkContractExpand(double,double) instead.
solve and
solveInPlace,
and throws an exception if one of the checks fails.
solve
and
solveInPlace,
and throws an exception if one of the checks fails.
representation can represent a valid chromosome.
representation can represent a valid chromosome.
representation can represent a valid chromosome.
observed and expected
frequency counts.
counts
array, viewed as a two-way table.
observed1 and observed2.
observed
frequency counts to those in the expected array.
alpha.
counts
array, viewed as a two-way table.
alpha.
observed1 and
observed2.
Chromosome objects.AbstractRandomGenerator.nextGaussian().
BitsStreamGenerator.nextGaussian.
valuesFileURL after use in REPLAY_MODE.
Clusterable points.Clusterable instances.
Cluster insteadClusterable insteadDistanceMeasure.
lambda must be
passed with the call to optimize (whereas in the current code it is set to an undocumented value).
lambda must be
passed with the call to optimize (whereas in the current code it is set to an undocumented value)..
lambda and inputSigma must be
passed with the call to optimize.
SimpleValueChecker.SimpleValueChecker()
lambda and inputSigma must be
passed with the call to optimize.
h(x[]) = combiner(...combiner(combiner(initialValue,f(x[0])),f(x[1]))...)
- collector(BivariateFunction, double) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Returns a MultivariateFunction h(x[]) defined by
h(x[]) = combiner(...combiner(combiner(initialValue,x[0]),x[1])...)
- cols -
Variable in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. As of 3.1.
- combine(BivariateFunction, UnivariateFunction, UnivariateFunction) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Returns the univariate function
h(x) = combiner(f(x), g(x)).
- combine(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Returns a new vector representing
a * this + b * y, the linear
combination of this and y.
- combine(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Returns a new vector representing
a * this + b * y, the linear
combination of this and y.
- combineToSelf(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Updates
this with the linear combination of this and
y.
- combineToSelf(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Updates
this with the linear combination of this and
y.
- comparatorPermutation(List<S>, Comparator<S>) -
Static method in class org.apache.commons.math3.genetics.RandomKey
- Generates a representation of a permutation corresponding to the
data sorted by comparator.
- compareTo(BigFraction) -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Compares this object to another based on size.
- compareTo(Fraction) -
Method in class org.apache.commons.math3.fraction.Fraction
- Compares this object to another based on size.
- compareTo(Chromosome) -
Method in class org.apache.commons.math3.genetics.Chromosome
- Compares two chromosomes based on their fitness.
- compareTo(OrderedTuple) -
Method in class org.apache.commons.math3.geometry.partitioning.utilities.OrderedTuple
- Compares this ordered T-uple with the specified object.
- compareTo(BigReal) -
Method in class org.apache.commons.math3.util.BigReal
-
- compareTo(Decimal64) -
Method in class org.apache.commons.math3.util.Decimal64
-
The current implementation returns the same value as
new Double(this.doubleValue()).compareTo(new
Double(o.doubleValue()))
- compareTo(double, double, double) -
Static method in class org.apache.commons.math3.util.Precision
- Compares two numbers given some amount of allowed error.
- compareTo(double, double, int) -
Static method in class org.apache.commons.math3.util.Precision
- Compares two numbers given some amount of allowed error.
- complainIfNotSupported(String) -
Method in class org.apache.commons.math3.ode.AbstractParameterizable
- Check if a parameter is supported and throw an IllegalArgumentException if not.
- complement(int) -
Method in class org.apache.commons.math3.dfp.Dfp
- Negate the mantissa of this by computing the complement.
- Complex - Class in org.apache.commons.math3.complex
- Representation of a Complex number, i.e. a number which has both a
real and imaginary part.
- Complex(double) -
Constructor for class org.apache.commons.math3.complex.Complex
- Create a complex number given only the real part.
- Complex(double, double) -
Constructor for class org.apache.commons.math3.complex.Complex
- Create a complex number given the real and imaginary parts.
- ComplexField - Class in org.apache.commons.math3.complex
- Representation of the complex numbers field.
- ComplexFormat - Class in org.apache.commons.math3.complex
- Formats a Complex number in cartesian format "Re(c) + Im(c)i".
- ComplexFormat() -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with the default imaginary character, 'i', and the
default number format for both real and imaginary parts.
- ComplexFormat(NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom number format for both real and
imaginary parts.
- ComplexFormat(NumberFormat, NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom number format for the real part and a
custom number format for the imaginary part.
- ComplexFormat(String) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom imaginary character, and the default
number format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom imaginary character, and a custom number
format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat, NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom imaginary character, a custom number
format for the real part, and a custom number format for the imaginary
part.
- ComplexUtils - Class in org.apache.commons.math3.complex
- Static implementations of common
Complex utilities functions. - compose(double...) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Compute composition of the instance by a univariate function.
- compose(double[], int, double[], double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute composition of a derivative structure by a function.
- compose(UnivariateFunction...) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Composes functions.
- compose(UnivariateDifferentiableFunction...) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Composes functions.
- compose(DifferentiableUnivariateFunction...) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Deprecated. as of 3.1 replaced by
FunctionUtils.compose(UnivariateDifferentiableFunction...)
- CompositeFormat - Class in org.apache.commons.math3.util
- Base class for formatters of composite objects (complex numbers, vectors ...).
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.CanberraDistance
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.ChebyshevDistance
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in interface org.apache.commons.math3.ml.distance.DistanceMeasure
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.EuclideanDistance
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.ManhattanDistance
- Compute the distance between two n-dimensional vectors.
- compute(MathArrays.Function) -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Performs an operation on the addressable elements of the array.
- computeCoefficients() -
Method in class org.apache.commons.math3.analysis.polynomials.PolynomialFunctionLagrangeForm
- Calculate the coefficients of Lagrange polynomial from the
interpolation data.
- computeCoefficients() -
Method in class org.apache.commons.math3.analysis.polynomials.PolynomialFunctionNewtonForm
- Calculate the normal polynomial coefficients given the Newton form.
- computeCorrelationMatrix(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Computes the correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Computes the correlation matrix for the columns of the
input rectangular array.
- computeCorrelationMatrix(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Computes the Spearman's rank correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) -
Method in class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Computes the Spearman's rank correlation matrix for the columns of the
input rectangular array.
- computeCost(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes the cost.
- computeCost(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes the cost.
- computeCovarianceMatrix(RealMatrix, boolean) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Compute a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(double[][], boolean) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Compute a covariance matrix from a rectangular array whose columns represent
covariates.
- computeCovarianceMatrix(double[][]) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a rectangular array whose columns represent
covariates.
- computeCovariances(double[], double) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Get the covariance matrix of the optimized parameters.
- computeCovariances(double[], double) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Get the covariance matrix of the optimized parameters.
- computeDerivativeObjectiveValue(double) -
Method in class org.apache.commons.math3.analysis.solvers.AbstractDifferentiableUnivariateSolver
- Deprecated. Compute the objective function value.
- computeDerivatives(double, double[], double[]) -
Method in class org.apache.commons.math3.ode.AbstractIntegrator
- Compute the derivatives and check the number of evaluations.
- computeDerivatives(double, double[], double[]) -
Method in class org.apache.commons.math3.ode.ExpandableStatefulODE
- Get the current time derivative of the complete state vector.
- computeDerivatives(double, double[], double[]) -
Method in class org.apache.commons.math3.ode.FirstOrderConverter
- Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) -
Method in interface org.apache.commons.math3.ode.FirstOrderDifferentialEquations
- Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[], double[], double[]) -
Method in interface org.apache.commons.math3.ode.SecondaryEquations
- Compute the derivatives related to the secondary state parameters.
- computeDistribution() -
Method in class org.apache.commons.math3.random.ValueServer
- Computes the empirical distribution using values from the file
in
valuesFileURL, using the default number of bins.
- computeDistribution(int) -
Method in class org.apache.commons.math3.random.ValueServer
- Computes the empirical distribution using values from the file
in
valuesFileURL and binCount bins.
- computeDividedDifference(double[], double[]) -
Static method in class org.apache.commons.math3.analysis.interpolation.DividedDifferenceInterpolator
- Return a copy of the divided difference array.
- computeExp(Dfp, Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpField
- Compute exp(a).
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.euclidean.oned.IntervalsSet
- Compute some geometrical properties.
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.PolyhedronsSet
- Compute some geometrical properties.
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.euclidean.twod.PolygonsSet
- Compute some geometrical properties.
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractRegion
- Compute some geometrical properties.
- computeInterpolatedStateAndDerivatives(double, double) -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) -
Method in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
- Compute the state and derivatives at the interpolated time.
- computeJacobian(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.JacobianMultivariateVectorOptimizer
- Computes the Jacobian matrix.
- computeLn(Dfp, Dfp, Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpField
- Compute ln(a).
- computeMainStateJacobian(double, double[], double[], double[][]) -
Method in interface org.apache.commons.math3.ode.MainStateJacobianProvider
- Compute the jacobian matrix of ODE with respect to main state.
- computeObjectiveGradient(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.scalar.GradientMultivariateOptimizer
- Compute the gradient vector.
- computeObjectiveGradient(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractDifferentiableOptimizer
- Deprecated. Compute the gradient vector.
- computeObjectiveGradient(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer
- Deprecated. Compute the gradient vector.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator
- Compute the objective function value.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.analysis.solvers.BaseAbstractUnivariateSolver
- Compute the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
- Computes the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer
- Computes the objective function value.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.optim.univariate.UnivariateOptimizer
- Computes the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
- Deprecated. Compute the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateVectorOptimizer
- Deprecated. Compute the objective function value.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.optimization.univariate.BaseAbstractUnivariateOptimizer
- Deprecated. Compute the objective function value.
- computeObjectiveValueAndDerivative(double) -
Method in class org.apache.commons.math3.analysis.solvers.AbstractUnivariateDifferentiableSolver
- Compute the objective function value.
- computeParameterJacobian(double, double[], double[], String, double[]) -
Method in interface org.apache.commons.math3.ode.ParameterJacobianProvider
- Compute the Jacobian matrix of ODE with respect to one parameter.
- computeResiduals(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes the residuals.
- computeResiduals(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes the residuals.
- computeRoots(int) -
Method in class org.apache.commons.math3.complex.RootsOfUnity
-
Computes the
n-th roots of unity.
- computeRule(int) -
Method in class org.apache.commons.math3.analysis.integration.gauss.BaseRuleFactory
- Computes the rule for the given order.
- computeRule(int) -
Method in class org.apache.commons.math3.analysis.integration.gauss.LegendreHighPrecisionRuleFactory
- Computes the rule for the given order.
- computeRule(int) -
Method in class org.apache.commons.math3.analysis.integration.gauss.LegendreRuleFactory
- Computes the rule for the given order.
- computeSecondDerivatives(double, double[], double[], double[]) -
Method in interface org.apache.commons.math3.ode.SecondOrderDifferentialEquations
- Get the current time derivative of the state vector.
- computeSigma(double[], double) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes an estimate of the standard deviation of the parameters.
- computeSigma(double[], double) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes an estimate of the standard deviation of the parameters.
- computeStepGrowShrinkFactor(double) -
Method in class org.apache.commons.math3.ode.MultistepIntegrator
- Compute step grow/shrink factor according to normalized error.
- computeWeightedJacobian(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes the weighted Jacobian matrix.
- computeWeightedJacobian(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes the Jacobian matrix.
- conjugate() -
Method in class org.apache.commons.math3.complex.Complex
- Return the conjugate of this complex number.
- ConjugateGradient - Class in org.apache.commons.math3.linear
-
This is an implementation of the conjugate gradient method for
RealLinearOperator. - ConjugateGradient(int, double, boolean) -
Constructor for class org.apache.commons.math3.linear.ConjugateGradient
- Creates a new instance of this class, with default
stopping criterion.
- ConjugateGradient(IterationManager, double, boolean) -
Constructor for class org.apache.commons.math3.linear.ConjugateGradient
- Creates a new instance of this class, with default
stopping criterion and custom iteration manager.
- ConjugateGradientFormula - Enum in org.apache.commons.math3.optimization.general
- Deprecated. As of 3.1 (to be removed in 4.0).
- Constant - Class in org.apache.commons.math3.analysis.function
- Constant function.
- Constant(double) -
Constructor for class org.apache.commons.math3.analysis.function.Constant
-
- CONSTANT_MODE -
Static variable in class org.apache.commons.math3.random.ValueServer
- Always return mu
- contains(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Line
- Check if the instance contains a point.
- contains(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Check if the instance contains a point.
- contains(Vector2D) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Check if the line contains a point.
- contains(Region<S>) -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractRegion
- Check if the instance entirely contains another region.
- contains(Region<S>) -
Method in interface org.apache.commons.math3.geometry.partitioning.Region
- Check if the instance entirely contains another region.
- containsClass(Class<?>) -
Method in class org.apache.commons.math3.util.TransformerMap
- Tests if a Class is present in the TransformerMap.
- containsKey(int) -
Method in class org.apache.commons.math3.util.OpenIntToDoubleHashMap
- Check if a value is associated with a key.
- containsKey(int) -
Method in class org.apache.commons.math3.util.OpenIntToFieldHashMap
- Check if a value is associated with a key.
- containsTransformer(NumberTransformer) -
Method in class org.apache.commons.math3.util.TransformerMap
- Tests if a NumberTransformer is present in the TransformerMap.
- ContinuedFraction - Class in org.apache.commons.math3.util
- Provides a generic means to evaluate continued fractions.
- ContinuedFraction() -
Constructor for class org.apache.commons.math3.util.ContinuedFraction
- Default constructor.
- ContinuousOutputModel - Class in org.apache.commons.math3.ode
- This class stores all information provided by an ODE integrator
during the integration process and build a continuous model of the
solution from this.
- ContinuousOutputModel() -
Constructor for class org.apache.commons.math3.ode.ContinuousOutputModel
- Simple constructor.
- contract() -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Contracts the storage array to the (size of the element set) + 1 - to
avoid a zero length array.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optim.AbstractConvergenceChecker
- Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in interface org.apache.commons.math3.optim.ConvergenceChecker
- Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optim.SimplePointChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointValuePair, PointValuePair) -
Method in class org.apache.commons.math3.optim.SimpleValueChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointVectorValuePair, PointVectorValuePair) -
Method in class org.apache.commons.math3.optim.SimpleVectorValueChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, UnivariatePointValuePair, UnivariatePointValuePair) -
Method in class org.apache.commons.math3.optim.univariate.SimpleUnivariateValueChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optimization.AbstractConvergenceChecker
- Deprecated. Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in interface org.apache.commons.math3.optimization.ConvergenceChecker
- Deprecated. Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optimization.SimplePointChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointValuePair, PointValuePair) -
Method in class org.apache.commons.math3.optimization.SimpleValueChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointVectorValuePair, PointVectorValuePair) -
Method in class org.apache.commons.math3.optimization.SimpleVectorValueChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- converged(int, UnivariatePointValuePair, UnivariatePointValuePair) -
Method in class org.apache.commons.math3.optimization.univariate.SimpleUnivariateValueChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- ConvergenceChecker<PAIR> - Interface in org.apache.commons.math3.optim
- This interface specifies how to check if an optimization algorithm has
converged.
- ConvergenceChecker<PAIR> - Interface in org.apache.commons.math3.optimization
- Deprecated. As of 3.1 (to be removed in 4.0).
- ConvergenceException - Exception in org.apache.commons.math3.exception
- Error thrown when a numerical computation can not be performed because the
numerical result failed to converge to a finite value.
- ConvergenceException() -
Constructor for exception org.apache.commons.math3.exception.ConvergenceException
- Construct the exception.
- ConvergenceException(Localizable, Object...) -
Constructor for exception org.apache.commons.math3.exception.ConvergenceException
- Construct the exception with a specific context and arguments.
- convertToComplex(double[]) -
Static method in class org.apache.commons.math3.complex.ComplexUtils
- Convert an array of primitive doubles to an array of
Complex objects.
- copy() -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.Array2DRowFieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.Array2DRowRealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.ArrayFieldVector
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Returns a (deep) copy of this vector.
- copy() -
Method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.BlockRealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.DiagonalMatrix
- Returns a (deep) copy of this.
- copy() -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in interface org.apache.commons.math3.linear.FieldVector
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.OpenMapRealMatrix
- Deprecated. Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.OpenMapRealVector
- Deprecated. Returns a (deep) copy of this vector.
- copy() -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.RealVector
- Returns a (deep) copy of this vector.
- copy() -
Method in class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Copy the instance.
- copy() -
Method in interface org.apache.commons.math3.ode.sampling.StepInterpolator
- Copy the instance.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.AbstractUnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
- Returns a copy of this DescriptiveStatistics instance with the same internal state.
- copy(DescriptiveStatistics, DescriptiveStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.GeometricMean
- Returns a copy of the statistic with the same internal state.
- copy(GeometricMean, GeometricMean) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.GeometricMean
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Kurtosis
- Returns a copy of the statistic with the same internal state.
- copy(Kurtosis, Kurtosis) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Kurtosis
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Mean
- Returns a copy of the statistic with the same internal state.
- copy(Mean, Mean) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Mean
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.SecondMoment
- Returns a copy of the statistic with the same internal state.
- copy(SecondMoment, SecondMoment) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.SecondMoment
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.SemiVariance
- Returns a copy of the statistic with the same internal state.
- copy(SemiVariance, SemiVariance) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.SemiVariance
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Returns a copy of the statistic with the same internal state.
- copy(Skewness, Skewness) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Returns a copy of the statistic with the same internal state.
- copy(StandardDeviation, StandardDeviation) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Variance
- Returns a copy of the statistic with the same internal state.
- copy(Variance, Variance) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Variance
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.rank.Max
- Returns a copy of the statistic with the same internal state.
- copy(Max, Max) -
Static method in class org.apache.commons.math3.stat.descriptive.rank.Max
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.rank.Min
- Returns a copy of the statistic with the same internal state.
- copy(Min, Min) -
Static method in class org.apache.commons.math3.stat.descriptive.rank.Min
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.rank.Percentile
- Returns a copy of the statistic with the same internal state.
- copy(Percentile, Percentile) -
Static method in class org.apache.commons.math3.stat.descriptive.rank.Percentile
- Copies source to dest.
- copy() -
Method in interface org.apache.commons.math3.stat.descriptive.StorelessUnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.Product
- Returns a copy of the statistic with the same internal state.
- copy(Product, Product) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.Product
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.Sum
- Returns a copy of the statistic with the same internal state.
- copy(Sum, Sum) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.Sum
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.SumOfLogs
- Returns a copy of the statistic with the same internal state.
- copy(SumOfLogs, SumOfLogs) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.SumOfLogs
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.SumOfSquares
- Returns a copy of the statistic with the same internal state.
- copy(SumOfSquares, SumOfSquares) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.SumOfSquares
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.SummaryStatistics
- Returns a copy of this SummaryStatistics instance with the same internal state.
- copy(SummaryStatistics, SummaryStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.SummaryStatistics
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- Returns a copy of this SynchronizedDescriptiveStatistics instance with the
same internal state.
- copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.SynchronizedSummaryStatistics
- Returns a copy of this SynchronizedSummaryStatistics instance with the
same internal state.
- copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.SynchronizedSummaryStatistics
- Copies source to dest.
- copy() -
Method in interface org.apache.commons.math3.stat.descriptive.UnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy(ResizableDoubleArray, ResizableDoubleArray) -
Static method in class org.apache.commons.math3.util.ResizableDoubleArray
- Copies source to dest, copying the underlying data, so dest is
a new, independent copy of source.
- copy() -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Returns a copy of the ResizableDoubleArray.
- copyOf(int[]) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copyOf(double[]) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copyOf(int[], int) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copyOf(double[], int) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copySelf() -
Method in class org.apache.commons.math3.geometry.euclidean.oned.OrientedPoint
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractRegion
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractSubHyperplane
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.partitioning.BSPTree
- Copy the instance.
- copySelf() -
Method in interface org.apache.commons.math3.geometry.partitioning.Hyperplane
- Copy the instance.
- copySelf() -
Method in interface org.apache.commons.math3.geometry.partitioning.Region
- Copy the instance.
- copySelf() -
Method in interface org.apache.commons.math3.geometry.partitioning.SubHyperplane
- Copy the instance.
- copySign(DerivativeStructure) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Returns the instance with the sign of the argument.
- copysign(Dfp, Dfp) -
Static method in class org.apache.commons.math3.dfp.Dfp
- Creates an instance that is the same as x except that it has the sign of y.
- copySign(Dfp) -
Method in class org.apache.commons.math3.dfp.Dfp
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in class org.apache.commons.math3.dfp.Dfp
- Returns the instance with the sign of the argument.
- copySign(T) -
Method in interface org.apache.commons.math3.RealFieldElement
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in interface org.apache.commons.math3.RealFieldElement
- Returns the instance with the sign of the argument.
- copySign(Decimal64) -
Method in class org.apache.commons.math3.util.Decimal64
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in class org.apache.commons.math3.util.Decimal64
- Returns the instance with the sign of the argument.
- copySign(double, double) -
Static method in class org.apache.commons.math3.util.FastMath
- Returns the first argument with the sign of the second argument.
- copySign(float, float) -
Static method in class org.apache.commons.math3.util.FastMath
- Returns the first argument with the sign of the second argument.
- copySign(byte, byte) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySign(short, short) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySign(int, int) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySign(long, long) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySubMatrix(int, int, int, int, T[][]) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Copy a submatrix.
- copySubMatrix(int, int, int, int, T[][]) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Copy a submatrix.
- correct(double[]) -
Method in class org.apache.commons.math3.filter.KalmanFilter
- Correct the current state estimate with an actual measurement.
- correct(RealVector) -
Method in class org.apache.commons.math3.filter.KalmanFilter
- Correct the current state estimate with an actual measurement.
- CorrelatedRandomVectorGenerator - Class in org.apache.commons.math3.random
- A
RandomVectorGenerator that generates vectors with with
correlated components. - CorrelatedRandomVectorGenerator(double[], RealMatrix, double, NormalizedRandomGenerator) -
Constructor for class org.apache.commons.math3.random.CorrelatedRandomVectorGenerator
- Builds a correlated random vector generator from its mean
vector and covariance matrix.
- CorrelatedRandomVectorGenerator(RealMatrix, double, NormalizedRandomGenerator) -
Constructor for class org.apache.commons.math3.random.CorrelatedRandomVectorGenerator
- Builds a null mean random correlated vector generator from its
covariance matrix.
- correlation(double[], double[]) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Computes the Pearson's product-moment correlation coefficient between the two arrays.
- correlation(double[], double[]) -
Method in class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Computes the Spearman's rank correlation coefficient between the two arrays.
- cos() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Cosine operation.
- cos(double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute cosine of a derivative structure.
- Cos - Class in org.apache.commons.math3.analysis.function
- Cosine function.
- Cos() -
Constructor for class org.apache.commons.math3.analysis.function.Cos
-
- cos() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
cosine
of this complex number.
- cos() -
Method in class org.apache.commons.math3.dfp.Dfp
- Cosine operation.
- cos(Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- computes the cosine of the argument.
- cos() -
Method in interface org.apache.commons.math3.RealFieldElement
- Cosine operation.
- cos() -
Method in class org.apache.commons.math3.util.Decimal64
- Cosine operation.
- cos(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Cosine function.
- cosh() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Hyperbolic cosine operation.
- cosh(double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute hyperbolic cosine of a derivative structure.
- Cosh - Class in org.apache.commons.math3.analysis.function
- Hyperbolic cosine function.
- Cosh() -
Constructor for class org.apache.commons.math3.analysis.function.Cosh
-
- cosh() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
hyperbolic cosine of this complex number.
- cosh() -
Method in class org.apache.commons.math3.dfp.Dfp
- Hyperbolic cosine operation.
- cosh() -
Method in interface org.apache.commons.math3.RealFieldElement
- Hyperbolic cosine operation.
- cosh() -
Method in class org.apache.commons.math3.util.Decimal64
- Hyperbolic cosine operation.
- cosh(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Compute the hyperbolic cosine of a number.
- cosine(RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Computes the cosine of the angle between this vector and the
argument.
- cosInternal(Dfp[]) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Computes cos(a) Used when 0 < a < pi/4.
- cost -
Variable in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. As of 3.1. Field to become "private" in 4.0.
Please use
AbstractLeastSquaresOptimizer.setCost(double).
- Covariance - Class in org.apache.commons.math3.stat.correlation
- Computes covariances for pairs of arrays or columns of a matrix.
- Covariance() -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a Covariance with no data
- Covariance(double[][], boolean) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(double[][]) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(RealMatrix, boolean) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a matrix whose columns
represent covariates.
- Covariance(RealMatrix) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a matrix whose columns
represent covariates.
- covariance(double[], double[], boolean) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Computes the covariance between the two arrays.
- covariance(double[], double[]) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Computes the covariance between the two arrays, using the bias-corrected
formula.
- covarianceToCorrelation(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Derives a correlation matrix from a covariance matrix.
- create(RealLinearOperator) -
Static method in class org.apache.commons.math3.linear.JacobiPreconditioner
- Creates a new instance of this class.
- createAdaptor(RandomGenerator) -
Static method in class org.apache.commons.math3.random.RandomAdaptor
- Factory method to create a
Random using the supplied
RandomGenerator.
- createBlocksLayout(Field<T>, int, int) -
Static method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Create a data array in blocks layout.
- createBlocksLayout(int, int) -
Static method in class org.apache.commons.math3.linear.BlockRealMatrix
- Create a data array in blocks layout.
- createChebyshevPolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Chebyshev polynomial of the first kind.
- createColumnFieldMatrix(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a column
FieldMatrix using the data from the input
array.
- createColumnRealMatrix(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a column
RealMatrix using the data from the input
array.
- createComplex(double, double) -
Method in class org.apache.commons.math3.complex.Complex
- Create a complex number given the real and imaginary parts.
- createComplexArray(double[][]) -
Static method in class org.apache.commons.math3.transform.TransformUtils
- Builds a new array of
Complex from the specified two dimensional
array of real and imaginary parts.
- createContributingStatistics() -
Method in class org.apache.commons.math3.stat.descriptive.AggregateSummaryStatistics
- Creates and returns a
SummaryStatistics whose data will be
aggregated with those of this AggregateSummaryStatistics.
- createFieldDiagonalMatrix(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a diagonal matrix with specified elements.
- createFieldIdentityMatrix(Field<T>, int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns
dimension x dimension identity matrix.
- createFieldMatrix(Field<T>, int, int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
FieldMatrix with specified dimensions.
- createFieldMatrix(T[][]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
FieldMatrix whose entries are the the values in the
the input array.
- createFieldVector(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a
FieldVector using the data from the input array.
- createHermitePolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Hermite polynomial.
- createJacobiPolynomial(int, int, int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Jacobi polynomial.
- createLaguerrePolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Laguerre polynomial.
- createLegendrePolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Legendre polynomial.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.Array2DRowFieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.Array2DRowRealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.BlockRealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.DiagonalMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.OpenMapRealMatrix
- Deprecated. Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createRealDiagonalMatrix(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a diagonal matrix with specified elements.
- createRealIdentityMatrix(int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns
dimension x dimension identity matrix.
- createRealImaginaryArray(Complex[]) -
Static method in class org.apache.commons.math3.transform.TransformUtils
- Builds a new two dimensional array of
double filled with the real
and imaginary parts of the specified Complex numbers.
- createRealMatrix(int, int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
RealMatrix with specified dimensions.
- createRealMatrix(double[][]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
RealMatrix whose entries are the the values in the
the input array.
- createRealVector(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a
RealVector using the data from the input array.
- createRowFieldMatrix(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Create a row
FieldMatrix using the data from the input
array.
- createRowRealMatrix(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Create a row
RealMatrix using the data from the input
array.
- crossover(Chromosome, Chromosome) -
Method in interface org.apache.commons.math3.genetics.CrossoverPolicy
- Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.CycleCrossover
- Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.NPointCrossover
- Performs a N-point crossover.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.OnePointCrossover
- Performs one point crossover.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.OrderedCrossover
- Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.UniformCrossover
- Perform a crossover operation on the given chromosomes.
- CrossoverPolicy - Interface in org.apache.commons.math3.genetics
- Policy used to create a pair of new chromosomes by performing a crossover
operation on a source pair of chromosomes.
- crossProduct(FieldVector3D<T>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of the instance with another vector.
- crossProduct(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of the instance with another vector.
- crossProduct(FieldVector3D<T>, FieldVector3D<T>) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of two vectors.
- crossProduct(FieldVector3D<T>, Vector3D) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of two vectors.
- crossProduct(Vector3D, FieldVector3D<T>) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of two vectors.
- crossProduct(Vector<Euclidean3D>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Vector3D
- Compute the cross-product of the instance with another vector.
- crossProduct(Vector3D, Vector3D) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.Vector3D
- Compute the cross-product of two vectors.
- cumulativeProbability(int, int) -
Method in class org.apache.commons.math3.distribution.AbstractIntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
- cumulativeProbability(double, double) -
Method in class org.apache.commons.math3.distribution.AbstractRealDistribution
- Deprecated. As of 3.1 (to be removed in 4.0). Please use
AbstractRealDistribution.probability(double,double) instead.
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.BetaDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.BinomialDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.CauchyDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.ChiSquaredDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.EnumeratedIntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.EnumeratedRealDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.ExponentialDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.FDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.GammaDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.HypergeometricDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in interface org.apache.commons.math3.distribution.IntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int, int) -
Method in interface org.apache.commons.math3.distribution.IntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.LevyDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.LogNormalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double, double) -
Method in class org.apache.commons.math3.distribution.LogNormalDistribution
- Deprecated. See
RealDistribution.cumulativeProbability(double,double)
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.NormalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double, double) -
Method in class org.apache.commons.math3.distribution.NormalDistribution
- Deprecated. See
RealDistribution.cumulativeProbability(double,double)
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.PascalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.PoissonDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in interface org.apache.commons.math3.distribution.RealDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double, double) -
Method in interface org.apache.commons.math3.distribution.RealDistribution
- Deprecated. As of 3.1. In 4.0, this method will be renamed
probability(double x0, double x1).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.TDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.TriangularDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.UniformIntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.UniformRealDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.WeibullDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.ZipfDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.random.EmpiricalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- currentState -
Variable in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- current state
- CurveFitter<T extends ParametricUnivariateFunction> - Class in org.apache.commons.math3.fitting
- Fitter for parametric univariate real functions y = f(x).
- CurveFitter(MultivariateVectorOptimizer) -
Constructor for class org.apache.commons.math3.fitting.CurveFitter
- Simple constructor.
- CurveFitter<T extends ParametricUnivariateFunction> - Class in org.apache.commons.math3.optimization.fitting
- Deprecated. As of 3.1 (to be removed in 4.0).
- CurveFitter(DifferentiableMultivariateVectorOptimizer) -
Constructor for class org.apache.commons.math3.optimization.fitting.CurveFitter
- Deprecated. as of 3.1 replaced by
CurveFitter.CurveFitter(MultivariateDifferentiableVectorOptimizer)
- CurveFitter(MultivariateDifferentiableVectorOptimizer) -
Constructor for class org.apache.commons.math3.optimization.fitting.CurveFitter
- Deprecated. Simple constructor.
- CycleCrossover<T> - Class in org.apache.commons.math3.genetics
- Cycle Crossover [CX] builds offspring from ordered chromosomes by identifying cycles
between two parent chromosomes.
- CycleCrossover() -
Constructor for class org.apache.commons.math3.genetics.CycleCrossover
- Creates a new
CycleCrossover policy.
- CycleCrossover(boolean) -
Constructor for class org.apache.commons.math3.genetics.CycleCrossover
- Creates a new
CycleCrossover policy using the given randomStart behavior.
DBSCANClusterer insteaddouble value in an object.sequence of objects of type T according to the
permutation this chromosome represents.
sequence of objects of type T according to the
permutation this chromosome represents.
CMAESOptimizer.checkFeasableCount: 0.
CMAESOptimizer.diagonalOnly: 0.
RealMatrix objects.
BOBYQAOptimizer.initialTrustRegionRadius: 10.0 .
BOBYQAOptimizer.initialTrustRegionRadius: 10.0 .
CMAESOptimizer.isActiveCMA: true.
CMAESOptimizer.maxIterations: 30000.
CMAESOptimizer.random.
CMAESOptimizer.stopFitness: 0.0.
BOBYQAOptimizer.stoppingTrustRegionRadius: 1.0E-8 .
BOBYQAOptimizer.stoppingTrustRegionRadius: 1.0E-8 .
FieldMatrixChangingVisitor interface.FieldMatrixPreservingVisitor interface.IterativeLinearSolverEvent.MeasurementModel for the use with a KalmanFilter.MeasurementModel, taking double arrays as input parameters for the
respective measurement matrix and noise.
MeasurementModel, taking RealMatrix objects
as input parameters for the respective measurement matrix and noise.
ProcessModel for the use with a KalmanFilter.ProcessModel, taking double arrays as input parameters.
ProcessModel, taking double arrays as input parameters.
ProcessModel, taking double arrays as input parameters.
RealMatrixChangingVisitor interface.RealMatrixPreservingVisitor interface.x.
x.
x.
X whose values are distributed according to
this distribution, this method returns P(X = x).
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
Acos.value(DerivativeStructure)
Acosh.value(DerivativeStructure)
Asin.value(DerivativeStructure)
Asinh.value(DerivativeStructure)
Atan.value(DerivativeStructure)
Atanh.value(DerivativeStructure)
Cbrt.value(DerivativeStructure)
Constant.value(DerivativeStructure)
Cos.value(DerivativeStructure)
Cosh.value(DerivativeStructure)
Exp.value(DerivativeStructure)
Expm1.value(DerivativeStructure)
Gaussian.value(DerivativeStructure)
HarmonicOscillator.value(DerivativeStructure)
Identity.value(DerivativeStructure)
Inverse.value(DerivativeStructure)
Log.value(DerivativeStructure)
Log10.value(DerivativeStructure)
Log1p.value(DerivativeStructure)
Logistic.value(DerivativeStructure)
Logit.value(DerivativeStructure)
Minus.value(DerivativeStructure)
Power.value(DerivativeStructure)
Sigmoid.value(DerivativeStructure)
Sin.value(DerivativeStructure)
Sinc.value(DerivativeStructure)
Sinh.value(DerivativeStructure)
Sqrt.value(DerivativeStructure)
Tan.value(DerivativeStructure)
Tanh.value(DerivativeStructure)
UnivariateFunction.
RealMatrix field in a class.
RealVector field in a class.
Dfp which hides the radix-10000 artifacts of the superclass.Dfp.MultivariateDifferentiableFunctionMultivariateDifferentiableVectorFunctionUnivariateDifferentiableFunctionUnivariateDifferentiableMatrixFunctionUnivariateDifferentiableSolverUnivariateDifferentiableVectorFunctiondifferential from a regular function.
differential from a regular vector function.
differential from a regular matrix function.
differential from a regular function.
differential from a regular matrix function.
differential from a regular vector function.
i initial elements of the array.
i last elements of the array.
Clusterable instances
with the configured DistanceMeasure.
Complex whose value is
(this / divisor).
Complex whose value is (this / divisor),
with divisor interpreted as a real number.
BigInteger,
ie this * 1 / bg, returning the result in reduced form.
int, ie
this * 1 / i, returning the result in reduced form.
long, ie
this * 1 / l, returning the result in reduced form.
v.
v.
Clusterable for points with double coordinates.Localizable interface, without localization.RealVector might lead to wrong results. Since there is no
satisfactory correction to this bug, this method is deprecated. Users who
want to preserve this feature are advised to implement
RealVectorPreservingVisitor (possibly ignoring corner cases for
the sake of efficiency).
RealVector might lead to wrong results. Since there is no
satisfactory correction to this bug, this method is deprecated. Users who
want to preserve this feature are advised to implement
RealVectorPreservingVisitor (possibly ignoring corner cases for
the sake of efficiency).
ElitisticListPopulation instance.
ElitisticListPopulation instance and initializes its inner chromosome list.
RandomGenerator as the source of random data.
RandomGenerator as the source of random data.
EmpiricalDistribution.EmpiricalDistribution(int,RandomGenerator) instead.
EmpiricalDistribution.EmpiricalDistribution(RandomGenerator) instead.
EnumeratedDistribution.EnumeratedDistribution.1 + EPSILON is numerically equal to 1.
object is a
FieldMatrix instance with the same dimensions as this
and all corresponding matrix entries are equal.
object is a
RealMatrix instance with the same dimensions as this
and all corresponding matrix entries are equal.
object is an
AbstractStorelessUnivariateStatistic returning the same
values as this for getResult() and getN()
object is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
object is a
StatisticalSummaryValues instance and all statistics have
the same values as this.
object is a
SummaryStatistics instance and all statistics have the
same values as this.
object is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
object is a
SummaryStatistics instance and all statistics have the
same values as this.
Precision.equals(float,float).
true iff both arguments are null or have same
dimensions and all their elements are equal as defined by
Precision.equals(double,double).
equals(x, y, 1).
equals(x, y, 1).
true if there is no double value strictly between the
arguments or the difference between them is within the range of allowed
error (inclusive).
this method.
true iff both arguments are null or have same
dimensions and all their elements are equal as defined by
this method.
equals(x, y, 1).
equals(x, y, maxUlps).
equals(x, y, 1).
equals(x, y, maxUlps).
true if there is no double value strictly between the
arguments or the reltaive difference between them is smaller or equal
to the given tolerance.
MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution).
DoublePoint insteadDoublePoint insteadAbstractStorelessUnivariateStatistic.clear(), then invokes
AbstractStorelessUnivariateStatistic.increment(double) in a loop over the the input array, and then uses
AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
AbstractStorelessUnivariateStatistic.clear(), then invokes
AbstractStorelessUnivariateStatistic.increment(double) in a loop over the specified portion of the input
array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
SemiVariance of the designated values against the mean, using
instance properties varianceDirection and biasCorrection.
SemiVariance for the entire array against the mean, using
the current value of the biasCorrection instance property.
SemiVariance of the designated values against the cutoff, using
instance properties variancDirection and biasCorrection.
SemiVariance of the designated values against the cutoff in the
given direction, using the current value of the biasCorrection instance property.
SemiVariance of the designated values against the cutoff
in the given direction with the provided bias correction.
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
pth percentile of the values
in the values array.
quantileth percentile of the
designated values in the values array.
pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
event handler.
event handler during integration steps.int.
ExceptionContext interface.ex-1 function.n.
Math and
StrictMath for large scale computation.Rotation using RealFieldElement.Vector3D using RealFieldElement.length with values generated
using getNext() repeatedly.
filtering events.population for another chromosome with the same representation.
PolynomialFitter.fit(double[]) instead.
FixedElapsedTime instance.
FixedElapsedTime instance.
float.
floor function.ComplexFormat.format(Object,StringBuffer,FieldPosition).
ComplexFormat.format(Object,StringBuffer,FieldPosition).
Complex object to produce a string.
BigFraction object to produce a string.
Fraction object to produce a string.
BigFraction object to produce a string.
Fraction object to produce a string.
Vector object to produce a string.
Vector3D object to produce a string.
Vector object to produce a string.
Vector object to produce a string.
Vector object to produce a string.
Vector to produce a string.
RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition).
RealMatrix object to produce a string.
RealVectorFormat.format(RealVector,StringBuffer,FieldPosition).
RealVector object to produce a string.
FieldMatrix/Fraction matrix to a RealMatrix.
observed and expected
frequency counts.
Gaussian function.norm, mean, and sigma
of a Gaussian.Parametric
based on the specified observed points.norm, mean, and sigma
of a Gaussian.Parametric
based on the specified observed points.integrating a weighted
function.points and weights.
Gaussian integration rule.SimpleVectorValueChecker.SimpleVectorValueChecker()
SimpleVectorValueChecker.SimpleVectorValueChecker()
observed1 and observed2.
GeometricMean identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
alpha.
GammaDistribution.getShape() should be preferred.
This method will be removed in version 4.0.
beta.
GammaDistribution.getScale() should be preferred.
This method will be removed in version 4.0.
SummaryStatistics instances containing
statistics describing the values in each of the bins.
true if positive-definiteness should be checked for both
matrix and preconditioner.
true if symmetry of the matrix, and symmetry as well as
positive definiteness of the preconditioner should be checked.
col as an array.
col as an array.
col as an array.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a vector.
column
as a vector.
column
as a vector.
ResizableDoubleArray.getContractionCriterion()
instead.
AbstractLeastSquaresOptimizer.computeCovariances(double[],double)
instead.
AbstractLeastSquaresOptimizer.computeCovariances(double[],double)
instead.
CrossoverPolicy.
FieldVector.toArray() method instead.
SparseFieldVector.toArray() method instead.
BigInteger.
DistanceMeasure instance used by this clusterer.
DoubleArray.
ResizableArray.
EmpiricalDistribution used when operating in 0.