RAT (Release Audit Tool) results

The following document contains the results of RAT (Release Audit Tool) .

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Summary
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Notes: 5
Binaries: 500
Archives: 0
Standards: 689

Apache Licensed: 656
Generated Documents: 1

JavaDocs are generated and so license header is optional
Generated files do not required license headers

32 Unknown Licenses

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Archives (+ indicates readable, $ unreadable): 

 
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  Files with AL headers will be marked L
  Binary files (which do not require AL headers) will be marked B
  Compressed archives will be marked A
  Notices, licenses etc will be marked N
  AL    checkstyle.xml
  AL    build.properties.sample
  GEN   build.xml
  AL    project.properties
  AL    src/experimental/org/apache/commons/math/util/BeanTransformerTest.java
  AL    src/experimental/org/apache/commons/math/util/BeanTransformer.java
  AL    src/experimental/org/apache/commons/math/analysis/UnivariateRealFunctionUtils.java
  AL    src/experimental/org/apache/commons/math/analysis/UnivariateRealFunctionUtilsTest.java
  AL    src/experimental/org/apache/commons/math/analysis/FunctionOperator.java
  AL    src/experimental/org/apache/commons/math/analysis/DerivativeOperatorFactory.java
  AL    src/experimental/org/apache/commons/math/analysis/UnivariateRealFunctionProxy.java
  AL    src/experimental/org/apache/commons/math/analysis/derivative/BackwardDifferenceDerivative.java
  AL    src/experimental/org/apache/commons/math/analysis/derivative/CenterDifferenceDerivative.java
  AL    src/experimental/org/apache/commons/math/analysis/derivative/AbstractDifferenceDerivative.java
  AL    src/experimental/org/apache/commons/math/analysis/derivative/ForwardDifferenceDerivative.java
  AL    src/experimental/org/apache/commons/math/analysis/DerivativeOperatorFactoryTest.java
  AL    src/experimental/org/apache/commons/math/stat/univariate/BeanListUnivariateImpl.java
  AL    src/experimental/org/apache/commons/math/stat/univariate/BeanListUnivariateImplTest.java
  AL    src/experimental/org/apache/commons/math/function/Evaluation.java
  AL    src/experimental/org/apache/commons/math/function/Variable.java
  AL    src/experimental/org/apache/commons/math/function/EvaluationException.java
  AL    src/experimental/org/apache/commons/math/function/EvaluationContext.java
  AL    src/experimental/org/apache/commons/math/function/Compilable.java
  AL    src/experimental/org/apache/commons/math/function/simple/Divide.java
  AL    src/experimental/org/apache/commons/math/function/simple/Add.java
  AL    src/experimental/org/apache/commons/math/function/simple/Subtract.java
  AL    src/experimental/org/apache/commons/math/function/simple/Power.java
  AL    src/experimental/org/apache/commons/math/function/simple/Sqrt.java
  AL    src/experimental/org/apache/commons/math/function/simple/Equals.java
  AL    src/experimental/org/apache/commons/math/function/simple/Multiply.java
  AL    src/experimental/org/apache/commons/math/function/DefaultContext.java
  AL    src/experimental/org/apache/commons/math/linear/CholeskySolverTest.java
  AL    src/experimental/org/apache/commons/math/linear/RealVector.java
  AL    src/experimental/org/apache/commons/math/linear/Decomposition.java
  AL    src/experimental/org/apache/commons/math/linear/CholeskySolver.java
  AL    src/experimental/org/apache/commons/math/linear/Decomposer.java
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  AL    src/site/xdoc/tasks.xml
  AL    src/site/xdoc/releases.xml
  AL    src/site/xdoc/developers.xml
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  AL    src/site/xdoc/userguide/geometry.xml
  AL    src/site/xdoc/userguide/overview.xml
  AL    src/site/xdoc/userguide/analysis.xml
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  AL    src/site/xdoc/userguide/optimization.xml
  AL    src/site/xdoc/userguide/estimation.xml
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  AL    src/site/resources/userguide/TrajectoryDeterminationProblem.java
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  AL    src/mantissa/tests-src/org/spaceroots/mantissa/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/fitting/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/fitting/AbstractCurveFitterTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/fitting/PolynomialFitterTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/fitting/HarmonicFitterTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/PolynomialRationalTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/PolynomialDoubleTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/LegendreTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/ChebyshevTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/HermiteTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/PolynomialFractionTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/RationalNumberTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/algebra/LaguerreTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/utilities/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/utilities/MappableArrayTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/utilities/IntervalTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/utilities/MappableScalarTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/utilities/ArrayMapperTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/utilities/IntervalsListTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/quadrature/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/quadrature/vectorial/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/quadrature/vectorial/GaussLegendreIntegratorTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/quadrature/scalar/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/quadrature/scalar/GaussLegendreIntegratorTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/LowerTriangularMatrixTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/SymetricalMatrixTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/UpperTriangularMatrixTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/MatrixFactoryTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/NonNullRangeTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/GeneralMatrixTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/DiagonalMatrixTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/linalg/GeneralSquareMatrixTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/random/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/random/ScalarSampleStatisticsTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/roots/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/roots/TestProblem.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/roots/BrentSolverTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/vectorial/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/vectorial/VectorialValuedPairTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/vectorial/ComputableFunctionSamplerTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/vectorial/BasicSampledFunctionIteratorTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/scalar/AllTests.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/scalar/ComputableFunctionSamplerTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/scalar/BasicSampledFunctionIteratorTest.java
  AL    src/mantissa/tests-src/org/spaceroots/mantissa/functions/scalar/ScalarValuedPairTest.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/PolynomialFitter.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/PolynomialCoefficient.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/HarmonicCoefficientsGuesser.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/F2FP2Iterator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/HarmonicFitter.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/FFPIterator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/fitting/AbstractCurveFitter.java
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  B     src/mantissa/src/org/spaceroots/mantissa/fitting/doc-files/org_spaceroots_mantissa_fitting_classes.png
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/Legendre.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/Polynomial.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/RationalNumber.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/Hermite.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/Laguerre.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/Chebyshev.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/OrthogonalPolynomial.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/CoefficientsGenerator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/algebra/PolynomialFraction.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/IntervalsList.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/Interval.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/MappableScalar.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/ArraySliceMappable.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/MappableArray.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/ArrayMapper.java
  AL    src/mantissa/src/org/spaceroots/mantissa/utilities/ArrayMapperEntry.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/SampledFunctionIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/RiemannIntegratorSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/RiemannIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/GaussLegendreIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/ComputableFunctionIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/TrapezoidIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/TrapezoidIntegratorSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/EnhancedSimpsonIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/vectorial/EnhancedSimpsonIntegratorSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/SampledFunctionIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/RiemannIntegratorSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/RiemannIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/GaussLegendreIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/ComputableFunctionIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/TrapezoidIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/TrapezoidIntegratorSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/EnhancedSimpsonIntegrator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/quadrature/scalar/EnhancedSimpsonIntegratorSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/GeneralMatrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/NonNullRange.java
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  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/GeneralSquareMatrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/SymetricalMatrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/SquareMatrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/MatrixFactory.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/LowerTriangularMatrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/DiagonalMatrix.java
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  B     src/mantissa/src/org/spaceroots/mantissa/linalg/doc-files/org_spaceroots_mantissa_linalg_classes.png
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/SingularMatrixException.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/Matrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/linalg/UpperTriangularMatrix.java
  AL    src/mantissa/src/org/spaceroots/mantissa/MessagesResources_fr.java
  AL    src/mantissa/src/org/spaceroots/mantissa/MessagesResources.java
  AL    src/mantissa/src/org/spaceroots/mantissa/random/ScalarSampleStatistics.java
  AL    src/mantissa/src/org/spaceroots/mantissa/random/VectorialSampleStatistics.java
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  B     src/mantissa/src/org/spaceroots/mantissa/random/doc-files/org_spaceroots_mantissa_random_classes.png
  AL    src/mantissa/src/org/spaceroots/mantissa/MantissaException.java
  AL    src/mantissa/src/org/spaceroots/mantissa/roots/RootsFinder.java
  AL    src/mantissa/src/org/spaceroots/mantissa/roots/ConvergenceChecker.java
  AL    src/mantissa/src/org/spaceroots/mantissa/roots/BrentSolver.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/vectorial/VectorialValuedPair.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/vectorial/SampledFunctionIterator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/vectorial/ComputableFunctionSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/vectorial/SampledFunction.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/vectorial/ComputableFunction.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/vectorial/BasicSampledFunctionIterator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/FunctionException.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/scalar/SampledFunctionIterator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/scalar/ComputableFunctionSampler.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/scalar/ScalarValuedPair.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/scalar/SampledFunction.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/scalar/ComputableFunction.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/scalar/BasicSampledFunctionIterator.java
  AL    src/mantissa/src/org/spaceroots/mantissa/functions/ExhaustedSampleException.java
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  AL    src/mantissa/LICENSE-2.0.txt
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  AL    src/java/org/apache/commons/math/estimation/WeightedMeasurement.java
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  AL    src/java/org/apache/commons/math/estimation/EstimationProblem.java
  AL    src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java
  AL    src/java/org/apache/commons/math/estimation/Estimator.java
  AL    src/java/org/apache/commons/math/estimation/EstimationException.java
  AL    src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java
  AL    src/java/org/apache/commons/math/estimation/AbstractEstimator.java
  AL    src/java/org/apache/commons/math/estimation/EstimatedParameter.java
  AL    src/java/org/apache/commons/math/estimation/package.html
  AL    src/java/org/apache/commons/math/DuplicateSampleAbscissaException.java
  AL    src/java/org/apache/commons/math/genetics/Population.java
  AL    src/java/org/apache/commons/math/genetics/GeneticAlgorithm.java
  AL    src/java/org/apache/commons/math/genetics/MutationPolicy.java
  AL    src/java/org/apache/commons/math/genetics/CrossoverPolicy.java
  AL    src/java/org/apache/commons/math/genetics/Fitness.java
  AL    src/java/org/apache/commons/math/genetics/StoppingCondition.java
  AL    src/java/org/apache/commons/math/genetics/SelectionPolicy.java
  AL    src/java/org/apache/commons/math/genetics/Chromosome.java
  AL    src/java/org/apache/commons/math/genetics/ChromosomePair.java
  AL    src/java/org/apache/commons/math/util/ResizableDoubleArray.java
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  AL    src/java/org/apache/commons/math/util/TransformerMap.java
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  AL    src/java/org/apache/commons/math/MathConfigurationException.java
  AL    src/java/org/apache/commons/math/distribution/DiscreteDistribution.java
  AL    src/java/org/apache/commons/math/distribution/Distribution.java
  AL    src/java/org/apache/commons/math/distribution/CauchyDistribution.java
  AL    src/java/org/apache/commons/math/distribution/BinomialDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/TDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/NormalDistribution.java
  AL    src/java/org/apache/commons/math/distribution/FDistributionImpl.java
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  AL    src/java/org/apache/commons/math/distribution/AbstractDistribution.java
  AL    src/java/org/apache/commons/math/distribution/ContinuousDistribution.java
  AL    src/java/org/apache/commons/math/distribution/ExponentialDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/FDistribution.java
  AL    src/java/org/apache/commons/math/distribution/PascalDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/WeibullDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/HypergeometricDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/PoissonDistributionImpl.java
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  AL    src/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java
  AL    src/java/org/apache/commons/math/distribution/GammaDistributionImpl.java
  AL    src/java/org/apache/commons/math/distribution/GammaDistribution.java
  AL    src/java/org/apache/commons/math/distribution/ChiSquaredDistributionImpl.java
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  AL    src/java/org/apache/commons/math/distribution/HypergeometricDistribution.java
  AL    src/java/org/apache/commons/math/distribution/PoissonDistribution.java
  AL    src/java/org/apache/commons/math/ConvergenceException.java
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  AL    src/java/org/apache/commons/math/analysis/LaguerreSolver.java
  AL    src/java/org/apache/commons/math/analysis/UnivariateRealSolverFactory.java
  AL    src/java/org/apache/commons/math/analysis/SecantSolver.java
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  AL    src/java/org/apache/commons/math/analysis/PolynomialFunctionNewtonForm.java
  AL    src/java/org/apache/commons/math/analysis/DividedDifferenceInterpolator.java
  AL    src/java/org/apache/commons/math/analysis/PolynomialFunction.java
  AL    src/java/org/apache/commons/math/analysis/RiddersSolver.java
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  AL    src/java/org/apache/commons/math/analysis/TrapezoidIntegrator.java
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 ==src/mantissa/src/org/spaceroots/mantissa/fitting/package.html
 =======================================================================
 <html>
<body>
This package provides classes to perform curve fitting.

<p>Curve fitting is a special case of an {@link
org.spaceroots.mantissa.estimation.EstimationProblem estimation problem}
were the parameters are the coefficients of a function <code>f</code>
whose graph <code>y=f(x)</code> should pass through sample points, and
were the measurements are the ordinates of the curve
<code>yi=f(xi)</code>.</p>

<p>The organisation of this package is explained in the class diagram
below. The {@link org.spaceroots.mantissa.fitting.AbstractCurveFitter
AbstractCurveFitter} class is the base class for all curve fitting
classes, it handles all common features like sample points
handling. Each specific curve fitting class should sub-class this
abstract class and implement the {@link
org.spaceroots.mantissa.fitting.AbstractCurveFitter#valueAt valueAt} and
{@link org.spaceroots.mantissa.fitting.AbstractCurveFitter#partial
partial} methods.</p>

<img src="doc-files/org_spaceroots_mantissa_fitting_classes.png" />

@author L. Maisonobe
</body>
</html>

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      <Foundation.Core.GeneralizableElement.isAbstract xmi.value="false"/>
      <Foundation.Core.Namespace.ownedElement>
        <Foundation.Extension_Mechanisms.Stereotype xmi.id="xmi.2">
          <Foundation.Core.ModelElement.name></Foundation.Core.ModelElement.name>
          <Foundation.Core.ModelElement.isSpecification xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isRoot xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isLeaf xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isAbstract xmi.value="false"/>
          <Foundation.Core.ModelElement.namespace>
            <Foundation.Core.Namespace xmi.idref="xmi.1"/>
          </Foundation.Core.ModelElement.namespace>
          <Foundation.Extension_Mechanisms.Stereotype.extendedElement>
            <Foundation.Core.ModelElement xmi.idref="xmi.1"/>
          </Foundation.Extension_Mechanisms.Stereotype.extendedElement>
        </Foundation.Extension_Mechanisms.Stereotype>
        <Foundation.Core.DataType xmi.id="xmi.3">
          <Foundation.Core.ModelElement.name>double</Foundation.Core.ModelElement.name>
          <Foundation.Core.ModelElement.isSpecification xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isRoot xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isLeaf xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isAbstract xmi.value="false"/>
          <Foundation.Core.ModelElement.namespace>
            <Foundation.Core.Namespace xmi.idref="xmi.1"/>
          </Foundation.Core.ModelElement.namespace>
        </Foundation.Core.DataType>
        <Foundation.Core.Class xmi.id="xmi.4" xmi.uuid="127-0-0-1-2d157f:e3465cec1e:-7ffb">
          <Foundation.Core.ModelElement.name>Matrix</Foundation.Core.ModelElement.name>
          <Foundation.Core.ModelElement.isSpecification xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isRoot xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isLeaf xmi.value="false"/>
          <Foundation.Core.GeneralizableElement.isAbstract xmi.value="true"/>
          <Foundation.Core.Class.isActive xmi.value="false"/>
          <Foundation.Core.ModelElement.namespace>
            <Foundation.Core.Namespace xmi.idref="xmi.1"/>
          </Foundation.Core.ModelElement.namespace>
          <Foundation.Core.ModelElement.clientDependency>
            <Foundation.Core.Dependency xmi.idref="xmi.5"/>
            <Foundation.Core.Dependency xmi.idref="xmi.6"/>
          </Foundation.Core.ModelElement.clientDependency>

 =======================================================================
 ==src/mantissa/src/org/spaceroots/mantissa/linalg/design/linalg_classdiagram1.pgml
 =======================================================================
 <?xml version="1.0" encoding="ISO-8859-1" ?>
<!DOCTYPE pgml SYSTEM "pgml.dtd">
<pgml description="uci.uml.visual.UMLClassDiagram|127-0-0-1-2d157f:e3465cec1e:-8000"
      name="overview"
>
  <group name="Fig0"
       description="uci.uml.visual.FigClass[9, 2, 247, 207]"
       href="127-0-0-1-2d157f:e3465cec1e:-7ffb"
       fill="1"
       fillcolor="-1"
       stroke="1"
       strokecolor="-16777216"
  >
    <private>
    </private>
    
    <rectangle name="Fig0.0"
      x="10"
      y="3"
      width="245"
      height="205"
      fill="1"
      fillcolor="-1"
      stroke="1"
      strokecolor="-16777216"
    />
    <text name="Fig0.1"
      x="9"
      y="2"
      fill="1"
      fillcolor="-1"
      stroke="1"
      strokecolor="-16777216"
      font="dialog.italic"
      textsize="9"
    >Matrix</text>
    <text name="Fig0.2"
      x="9"
      y="16"
      fill="1"
      fillcolor="-1"
      stroke="1"
      strokecolor="-16777216"
      font="dialog"
      textsize="9"
    >protected int rows_
protected int columns_
protected double[] data_</text>
    <text name="Fig0.3"
      x="9"

 =======================================================================
 ==src/mantissa/src/org/spaceroots/mantissa/linalg/package.html
 =======================================================================
 <html>
<body>
This package provides classes to perform linear algebra computation.

<p>It is by no means a complete linear algebra system, it is
sufficient to solve least squares problems and linear equations
systems, but it lacks lots of functionalities and matrices types (for
example sparse matrices are not supported).</p>

<p>The class diagram for the public classes of this package is
displayed below. The user will mainly use directly the implementation
classes rather than the abstract {@link
org.spaceroots.mantissa.linalg.Matrix} class. The shape of the matrices
used is often known in the algorithms so there is little need to hide
this shape behind the general class.</p>

<img src="doc-files/org_spaceroots_mantissa_linalg_classes.png" />

@author L. Maisonobe
</body>
</html>

 =======================================================================
 ==src/mantissa/src/org/spaceroots/mantissa/random/package.html
 =======================================================================
 <html>
<body>
This package provides classes to perform some random draws and
statistical anaysis.

<p>The aim of this package is to provide the basic components needed
to generate random variables (correlated or not in the case of
vectorial variables) that could be used in a simulation application
and to provide some basic statistical classes in order to analyze the
simulation results.</p>

<p>Vectorial generators are build by embedding a {@link
org.spaceroots.mantissa.random.NormalizedRandomGenerator normalized}
scalar generator into the vectorial generator classes {@link
org.spaceroots.mantissa.random.CorrelatedRandomVectorGenerator
CorrelatedRandomVectorGenerator} or {@link
org.spaceroots.mantissa.random.UncorrelatedRandomVectorGenerator
UncorrelatedRandomVectorGenerator} that will be responsible for
packaging all numbers into vectors with the specified mean values, standard
deviations and correlation coefficients. Since most practical problems
make the assumption the probability distribution is a gaussian one,
the normalized generator will often be an instance of {@link
org.spaceroots.mantissa.random.GaussianRandomGenerator
GaussianRandomGenerator}, but uniform distribution are also available
using instances of {@link
org.spaceroots.mantissa.random.UniformRandomGenerator
UniformRandomGenerator}.</p>

<img src="doc-files/org_spaceroots_mantissa_random_classes.png" />

@author L. Maisonobe
</body>
</html>

 =======================================================================
 ==src/conf/manifestMods.txt
 =======================================================================
 Build-Jdk: 1.3.1_16
Specification-Version: 1.1
Implementation-Vendor-Id: org.apache

 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/NumAcc3.txt
 =======================================================================
 File Name:     NumAcc3.dat

File Format:   ASCII
               Header          : lines  1 to   60     (=   60)
               Certified Values: lines 41 to   43     (=    3)
               Data            : lines 61 to 1061     (= 1001)

Dataset Name:  NumAcc3

Description:   This is a constructed/fabricated data set
               to test accuracy in summary statistic calculations.
               The numbers are 8-digit floating point values and
               differ only in the last decimal place.
               Note--by construction, this data set has
                     sample mean            =  1000000.2   (exact)
                     sample standard dev.   =        0.1   (exact)
                     sample autocorr. coef. =     -0.999   (exact)

Stat Category: Univariate: Summary Statistics

Reference:     Simon, Stephen D. and Lesage, James P. (1989).
               Assessing the Accuracy of ANOVA Caluclations
               in Statistical Software", Computational
               Statistics & data Analysis, 8, pp. 325-332.


Data:          Constructed
               1    Response           : y
               0    Predictors
               1001 Observations

Model:         Average Level of Difficulty
               2    Parameters         : mu, sigma
               1    Response Variable  : y
               0    Predictor Variables

               y    = mu + e


                                                  Certified Values
Sample Mean                                ybar:  1000000.2 
Sample Standard Deviation (denom. = n-1)      s:  0.1       
Sample Autocorrelation Coefficient (lag 1) r(1): -0.999     

Number of Observations:                             1001






 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/Mavro.txt
 =======================================================================
 File Name:     Mavro.dat

File Format:   ASCII
               Header          : lines  1 to  60     (= 60)
               Certified Values: lines 41 to  43     (=  3)
               Data            : lines 61 to 110     (= 50)

Dataset Name:  Mavro (Filter Transmittance Data)

Description:   This is an observed/"real world" data set
               consisting of 50 transmittance measurements
               (at a sampling rate of 10 observations per second)
               from a filter with a nominal value of 2.
               The experimenter was Radu Mavrodineaunu,
               a member of the chemistry staff at NIST.
               We here use this data to test accuracy
               in summary statistics calculations.

Stat Category: Univariate: Summary Statistics

Reference:     None

Data:          "Real World"
               1    Response          : y = transmittance
               0    Predictors
               50   Observations

Model:         Lower Level of Difficulty
               2    Parameters        : mu, sigma
               1    Response Variable : y
               0    Predictor Variables

               y    = mu + e






                                                  Certified Values
Sample Mean                                ybar:  2.00185600000000
Sample Standard Deviation (denom. = n-1)      s:  0.000429123454003053
Sample Autocorrelation Coefficient (lag 1) r(1):  0.937989183438248

Number of Observations:                              50






 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/Lottery.txt
 =======================================================================
 #####################################################################
# Dataset Name:  Lottery
#
#Description:   This is an observed/"real world" data set
#               consisting of 218 lottery values
#               from September 3, 1989 to April 14, 1990 (32 weeks).
#               One 3-digit random number (from 000 to 999)
#               is drawn per day, 7 days per week for most
#               weeks, but fewer days per week for some weeks.
#               We here use this data to test accuracy
#               in summary statistics calculations.
#
# Stat Category: Univariate: Summary Statistics
#
# Reference:     http://www.itl.nist.gov/div898/strd/univ/lottery.html
#
# Data:          "Real World"
#               1    Response          : y = 3-digit random number
#               0    Predictors
#               218  Observations
#
# Model:         Lower Level of Difficulty
#               2    Parameters        : mu, sigma
#               1    Response Variable : y
#               0    Predictor Variables#
#               y    = mu + e
#####################################################################

#####################################################################
#
# Certified Values
#
#####################################################################
mean                       = 518.958715596330
standardDeviation          = 291.699727470969
autocorrelationCoefficient =  -0.120948622967393
n                          = 218

#####################################################################
#
# Data
#
#####################################################################
     162
     671
     933
     414
     788
     730
     817

 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/Lew.txt
 =======================================================================
 #####################################################################
# Dataset Name:  Lew (Beam Deflection Data)
#
# Description:   This is an observed/"real world" data set
#               consisting of 200 deflections of a steel-concrete
#               beam while subjected to periodic pressure.
#               The experimenter was H. S. Lew of the
#               Center for Building Technology at NIST.
#               We here use this data to test accuracy
#               in summary statistics calculations.
#
# Stat Category: Univariate: Summary Statistics
#
# Reference:     http://www.itl.nist.gov/div898/strd/univ/lew.html
#
# Data:         "Real World"
#               1    Response          : y = beam deflection
#               0    Predictors
#               200  Observations
#
# Model:        Lower Level of Difficulty
#               2    Parameters        : mu, sigma
#               1    Response Variable : y
#               0    Predictor Variables
#               y    = mu + e
#####################################################################

#####################################################################
#
# Certified Values
#
#####################################################################
n                          =  200
mean                       = -177.435000000000
standardDeviation          =  277.332168044316
autocorrelationCoefficient = -0.307304800605679

#####################################################################
#
# R Generated Values
#
#####################################################################
variance =  76913.13143
max      =  300
min      = -579
sum      = -35487

#####################################################################
#
# Data

 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/Michelso.txt
 =======================================================================
 File Name:     Michelso.dat

File Format:   ASCII
               Header          : lines  1 to  60     (=  60)
               Certified Values: lines 41 to  43     (=   3)
               Data            : lines 61 to 160     (= 100)

Dataset Name:  Michelso (Speed of Light Data, in millions of meters per second)

Description:   This is an observed/"real world" data set
               consisting of 100 measurements of the
               speed of light in air.  This classic experiment
               was carried out by Michelson is 1879.
               We here use this data to test accuracy
               in summary statistics calculations.

Stat Category: Univariate: Summary Statistics

Reference:     Dorsey, Ernest N. (1944). The Velocity of Light.
               Transactions of the American Philiosophical
               Society, Volume 34, Part 1, Pages 1-110, Table 22.

               y    = mu + e
















                                                  Certified Values
Sample Mean                                ybar:  299.852400000000
Sample Standard Deviation (denom. = n-1)      s:  0.0790105478190518
Sample Autocorrelation Coefficient (lag 1) r(1):  0.535199668621283

Number of Observations:                             100






 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/PiDigits.txt
 =======================================================================
 File Name:     PiDigits.dat

File Format:   ASCII
               Header          : lines  1 to   60     (=   60)
               Certified Values: lines 41 to   43     (=    3)
               Data            : lines 61 to 5060     (= 5000)

Dataset Name:  PiDigits

Description:   This is a constructed/fabricated data set
               to test accuracy in summary statistic calculations.
               The numbers are the first 5000 digits of the
               mathematical constant pi (= 3.1415926535897932384...).

Stat Category: Univariate

Reference:     Mathematics of Computation.
               January 1962, page 76.

Data:          Constructed Variable
               -->    1 Response           : y = pi digits
               -->    0 Predictors
               --> 5000 Observations

Model:         Lower Level of Difficulty
               -->    2 Parameters         : mu, sigma
               -->    1 Response  Variable : y
               -->    0 Predictor Variables

               y    = mu + e









                                                  Certified Values
Sample Mean                                ybar:  4.53480000000000
Sample Standard Deviation (denom. = n-1)      s:  2.86733906028871
Sample Autocorrelation Coefficient (lag 1) r(1): -0.00355099287237972

Number of Observations:                           5000






 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/NumAcc4.txt
 =======================================================================
 File Name:     NumAcc4.dat

File Format:   ASCII
               Header          : lines  1 to   60     (=   60)
               Certified Values: lines 41 to   43     (=    3)
               Data            : lines 61 to 1061     (= 1001)

Dataset Name:  NumAcc4

Description:   This is a constructed/fabricated data set
               to test accuracy in summary statistic calculations.
               The numbers are 9-digit floating point values and
               differ only in the last decimal place.
                     sample mean            =  10000000.2   (exact)
                     sample standard dev.   =         0.1   (exact)
                     sample autocorr. coef. =      -0.999   (exact)

Stat Category: Univariate

Reference:     Simon, Stephen D. and Lesage, James P. (1989).
               Assessing the Accuracy of ANOVA Caluclations
               in Statistical Software", Computational
               Statistics & data Analysis, 8, pp. 325-332.

Data:          Constructed
               1    Response           : y
               0    Predictors
               1001 Observations

Model:         Higher Level of Difficulty
               2    Parameters         : mu, sigma
               1    Response Variable  : y
               0    Predictor Variables

               y    = mu + e




                                                  Certified Values
Sample Mean                                ybar:   10000000.2 
Sample Standard Deviation (denom. = n-1)      s:   0.1        
Sample Autocorrelation Coefficient (lag 1) r(1):   -0.999     

Number of Observations:                             1001






 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/NumAcc2.txt
 =======================================================================
 File Name:     NumAcc2.dat

File Format:   ASCII
               Header          : lines  1 to   60     (=   60)
               Certified Values: lines 41 to   43     (=    3)
               Data            : lines 61 to 1061     (= 1001)

Dataset Name:  NumAcc2

Description:   This is a constructed/fabricated data set
               to test accuracy in summary statistic calculations.
               The numbers are 2-digit floating point values and
               differ only in the last decimal place.
               Note--by construction, this data set has
                     sample mean                  =  1.2   (exact)
                     sample standard deviation    =  0.1   (exact)
                     sample autocorrelation coef. = -0.999 (exact)

Stat Category: Univariate

Reference:     Simon, Stephen D. and Lesage, James P. (1989).
               Assessing the Accuracy of ANOVA Caluclations
               in Statistical Software", Computational
               Statistics & data Analysis, 8, pp. 325-332.


Data:          Constructed
               1    Response           : y
               0    Predictors
               1001 Observations

Model:         Average Level of Difficulty
               2    Parameters         : mu, sigma
               1    Response Variable  : y
               0    Predictor Variables

               y    = mu + e


                                                  Certified Values
Sample Mean                                ybar:  1.2   
Sample Standard Deviation (denom. = n-1)      s:  0.1    
Sample Autocorrelation Coefficient (lag 1) r(1):  -0.999 

Number of Observations:                             1001






 =======================================================================
 ==src/test/org/apache/commons/math/stat/data/NumAcc1.txt
 =======================================================================
 File Name:     NumAcc1.dat

File Format:   ASCII
               Header          : lines  1 to 60       (= 60)
               Certified Values: lines 41 to 43       (=  3)
               Data            : lines 61 to 63       (=  3)

Dataset Name:  NumAcc1

Description:   This is a constructed/fabricated data set
               to test accuracy in summary statistic calculations.
               The numbers are large (8-digit integers) and
               differ only in the last decimal place.
               Note--by construction, this data set has
                     sample mean                  = 10000002 (exact)
                     sample standard deviation    =        1 (exact)
                     sample autocorrelation coef. =     -0.5 (exact)

Stat Category: Univariate: Summary Statistics

Reference:     Simon, Stephen D. and Lesage, James P. (1989).
               Assessing the Accuracy of ANOVA Caluclations
               in Statistical Software", Computational
               Statistics & data Analysis, 8, pp. 325-332.

Data:          Constructed
               1    Response           : y
               0    Predictors
               3    Observations

Model:         Lower Level of Difficulty
               2    Parameters         : mu, sigma
               1    Response Variable  : y
               0    Predictor Variables

               y    = mu + e



                                                  Certified Values
Sample Mean                                ybar:  10000002 
Sample Standard Deviation (denom. = n-1)      s:         1 
Sample Autocorrelation Coefficient (lag 1) r(1):      -0.5 

Number of Observations:                                       3






 ======================