DescriptiveStatistics (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

All Implemented Interfaces:

Serializable, StatisticalSummary

Direct Known Subclasses:

SynchronizedDescriptiveStatistics
```
public class DescriptiveStatistics
extends Object
implements StatisticalSummary, Serializable
```
Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data. The windowSize property sets a limit on the number of values that can be stored in the dataset. The default value, INFINITE_WINDOW, puts no limit on the size of the dataset. This value should be used with caution, as the backing store will grow without bound in this case. For very large datasets, SummaryStatistics, which does not store the dataset, should be used instead of this class. If windowSize is not INFINITE_WINDOW and more values are added than can be stored in the dataset, new values are added in a "rolling" manner, with new values replacing the "oldest" values in the dataset.
Note: this class is not threadsafe. Use SynchronizedDescriptiveStatistics if concurrent access from multiple threads is required.

See Also:
Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

static int INFINITE_WINDOW
Represents an infinite window size.

protected int windowSize
hold the window size

Fields
Modifier and Type	Field and Description
`static int`	`INFINITE_WINDOW` Represents an infinite window size.
`protected int`	`windowSize` hold the window size

Constructor Summary

Constructors
Constructor and Description
`DescriptiveStatistics()` Construct a DescriptiveStatistics instance with an infinite window
`DescriptiveStatistics(DescriptiveStatistics original)` Copy constructor.
`DescriptiveStatistics(double[] initialDoubleArray)` Construct a DescriptiveStatistics instance with an infinite window and the initial data values in double[] initialDoubleArray.
`DescriptiveStatistics(int window)` Construct a DescriptiveStatistics instance with the specified window

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`addValue(double v)` Adds the value to the dataset.
`double`	`apply(UnivariateStatistic stat)` Apply the given statistic to the data associated with this set of statistics.
`void`	`clear()` Resets all statistics and storage
`DescriptiveStatistics`	`copy()` Returns a copy of this DescriptiveStatistics instance with the same internal state.
`static void`	`copy(DescriptiveStatistics source, DescriptiveStatistics dest)` Copies source to dest.
`double`	`getElement(int index)` Returns the element at the specified index
`double`	`getGeometricMean()` Returns the geometric mean of the available values.
`UnivariateStatistic`	`getGeometricMeanImpl()` Returns the currently configured geometric mean implementation.
`double`	`getKurtosis()` Returns the Kurtosis of the available values.
`UnivariateStatistic`	`getKurtosisImpl()` Returns the currently configured kurtosis implementation.
`double`	`getMax()` Returns the maximum of the available values
`UnivariateStatistic`	`getMaxImpl()` Returns the currently configured maximum implementation.
`double`	`getMean()` Returns the arithmetic mean of the available values
`UnivariateStatistic`	`getMeanImpl()` Returns the currently configured mean implementation.
`double`	`getMin()` Returns the minimum of the available values
`UnivariateStatistic`	`getMinImpl()` Returns the currently configured minimum implementation.
`long`	`getN()` Returns the number of available values
`double`	`getPercentile(double p)` Returns an estimate for the pth percentile of the stored values.
`UnivariateStatistic`	`getPercentileImpl()` Returns the currently configured percentile implementation.
`double`	`getPopulationVariance()` Returns the population variance of the available values.
`double`	`getQuadraticMean()` Returns the quadratic mean, a.k.a.
`double`	`getSkewness()` Returns the skewness of the available values.
`UnivariateStatistic`	`getSkewnessImpl()` Returns the currently configured skewness implementation.
`double[]`	`getSortedValues()` Returns the current set of values in an array of double primitives, sorted in ascending order.
`double`	`getStandardDeviation()` Returns the standard deviation of the available values.
`double`	`getSum()` Returns the sum of the values that have been added to Univariate.
`UnivariateStatistic`	`getSumImpl()` Returns the currently configured sum implementation.
`double`	`getSumsq()` Returns the sum of the squares of the available values.
`UnivariateStatistic`	`getSumsqImpl()` Returns the currently configured sum of squares implementation.
`double[]`	`getValues()` Returns the current set of values in an array of double primitives.
`double`	`getVariance()` Returns the (sample) variance of the available values.
`UnivariateStatistic`	`getVarianceImpl()` Returns the currently configured variance implementation.
`int`	`getWindowSize()` Returns the maximum number of values that can be stored in the dataset, or INFINITE_WINDOW (-1) if there is no limit.
`void`	`removeMostRecentValue()` Removes the most recent value from the dataset.
`double`	`replaceMostRecentValue(double v)` Replaces the most recently stored value with the given value.
`void`	`setGeometricMeanImpl(UnivariateStatistic geometricMeanImpl)` Sets the implementation for the gemoetric mean.
`void`	`setKurtosisImpl(UnivariateStatistic kurtosisImpl)` Sets the implementation for the kurtosis.
`void`	`setMaxImpl(UnivariateStatistic maxImpl)` Sets the implementation for the maximum.
`void`	`setMeanImpl(UnivariateStatistic meanImpl)` Sets the implementation for the mean.
`void`	`setMinImpl(UnivariateStatistic minImpl)` Sets the implementation for the minimum.
`void`	`setPercentileImpl(UnivariateStatistic percentileImpl)` Sets the implementation to be used by `getPercentile(double)`.
`void`	`setSkewnessImpl(UnivariateStatistic skewnessImpl)` Sets the implementation for the skewness.
`void`	`setSumImpl(UnivariateStatistic sumImpl)` Sets the implementation for the sum.
`void`	`setSumsqImpl(UnivariateStatistic sumsqImpl)` Sets the implementation for the sum of squares.
`void`	`setVarianceImpl(UnivariateStatistic varianceImpl)` Sets the implementation for the variance.
`void`	`setWindowSize(int windowSize)` WindowSize controls the number of values that contribute to the reported statistics.
`String`	`toString()` Generates a text report displaying univariate statistics from values that have been added.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - INFINITE_WINDOW
```
public static final int INFINITE_WINDOW
```
    Represents an infinite window size. When the getWindowSize() returns this value, there is no limit to the number of data values that can be stored in the dataset.
    
    See Also:
    Constant Field Values
  - windowSize
```
protected int windowSize
```
    hold the window size
- Constructor Detail
  - DescriptiveStatistics
```
public DescriptiveStatistics()
```
    Construct a DescriptiveStatistics instance with an infinite window
  - DescriptiveStatistics
```
public DescriptiveStatistics(int window)
                      throws MathIllegalArgumentException
```
    Construct a DescriptiveStatistics instance with the specified window
    
    Parameters:
    window - the window size.
    
    Throws:
    
    MathIllegalArgumentException - if window size is less than 1 but not equal to INFINITE_WINDOW
  - DescriptiveStatistics
```
public DescriptiveStatistics(double[] initialDoubleArray)
```
    Construct a DescriptiveStatistics instance with an infinite window and the initial data values in double[] initialDoubleArray. If initialDoubleArray is null, then this constructor corresponds to DescriptiveStatistics()
    
    Parameters:
    initialDoubleArray - the initial double[].
  - DescriptiveStatistics
```
public DescriptiveStatistics(DescriptiveStatistics original)
                      throws NullArgumentException
```
    Copy constructor. Construct a new DescriptiveStatistics instance that is a copy of original.
    
    Parameters:
    original - DescriptiveStatistics instance to copy
    
    Throws:
    
    NullArgumentException - if original is null
- Method Detail
  - addValue
```
public void addValue(double v)
```
    Adds the value to the dataset. If the dataset is at the maximum size (i.e., the number of stored elements equals the currently configured windowSize), the first (oldest) element in the dataset is discarded to make room for the new value.
    
    Parameters:
    v - the value to be added
  - removeMostRecentValue
```
public void removeMostRecentValue()
                           throws MathIllegalStateException
```
    Removes the most recent value from the dataset.
    
    Throws:
    
    MathIllegalStateException - if there are no elements stored
  - replaceMostRecentValue
```
public double replaceMostRecentValue(double v)
                              throws MathIllegalStateException
```
    Replaces the most recently stored value with the given value. There must be at least one element stored to call this method.
    
    Parameters:
    v - the value to replace the most recent stored value
    
    Returns:
    replaced value
    
    Throws:
    
    MathIllegalStateException - if there are no elements stored
  - getMean
```
public double getMean()
```
    Returns the arithmetic mean of the available values
    
    Specified by:
    
    getMean in interface StatisticalSummary
    
    Returns:
    The mean or Double.NaN if no values have been added.
  - getGeometricMean
```
public double getGeometricMean()
```
    Returns the geometric mean of the available values.
    See GeometricMean for details on the computing algorithm.
    
    Returns:
    The geometricMean, Double.NaN if no values have been added, or if any negative values have been added.
  - getVariance
```
public double getVariance()
```
    Returns the (sample) variance of the available values.
    This method returns the bias-corrected sample variance (using n - 1 in the denominator). Use getPopulationVariance() for the non-bias-corrected population variance.
    
    Specified by:
    
    getVariance in interface StatisticalSummary
    
    Returns:
    The variance, Double.NaN if no values have been added or 0.0 for a single value set.
  - getPopulationVariance
```
public double getPopulationVariance()
```
    Returns the population variance of the available values.
    
    Returns:
    The population variance, Double.NaN if no values have been added, or 0.0 for a single value set.
  - getStandardDeviation
```
public double getStandardDeviation()
```
    Returns the standard deviation of the available values.
    
    Specified by:
    
    getStandardDeviation in interface StatisticalSummary
    
    Returns:
    The standard deviation, Double.NaN if no values have been added or 0.0 for a single value set.
  - getQuadraticMean
```
public double getQuadraticMean()
```
    Returns the quadratic mean, a.k.a. root-mean-square of the available values
    
    Returns:
    The quadratic mean or Double.NaN if no values have been added.
  - getSkewness
```
public double getSkewness()
```
    Returns the skewness of the available values. Skewness is a measure of the asymmetry of a given distribution.
    
    Returns:
    The skewness, Double.NaN if less than 3 values have been added.
  - getKurtosis
```
public double getKurtosis()
```
    Returns the Kurtosis of the available values. Kurtosis is a measure of the "peakedness" of a distribution.
    
    Returns:
    The kurtosis, Double.NaN if less than 4 values have been added.
  - getMax
```
public double getMax()
```
    Returns the maximum of the available values
    
    Specified by:
    
    getMax in interface StatisticalSummary
    
    Returns:
    The max or Double.NaN if no values have been added.
  - getMin
```
public double getMin()
```
    Returns the minimum of the available values
    
    Specified by:
    
    getMin in interface StatisticalSummary
    
    Returns:
    The min or Double.NaN if no values have been added.
  - getN
```
public long getN()
```
    Returns the number of available values
    
    Specified by:
    
    getN in interface StatisticalSummary
    
    Returns:
    The number of available values
  - getSum
```
public double getSum()
```
    Returns the sum of the values that have been added to Univariate.
    
    Specified by:
    
    getSum in interface StatisticalSummary
    
    Returns:
    The sum or Double.NaN if no values have been added
  - getSumsq
```
public double getSumsq()
```
    Returns the sum of the squares of the available values.
    
    Returns:
    The sum of the squares or Double.NaN if no values have been added.
  - clear
```
public void clear()
```
    Resets all statistics and storage
  - getWindowSize
```
public int getWindowSize()
```
    Returns the maximum number of values that can be stored in the dataset, or INFINITE_WINDOW (-1) if there is no limit.
    
    Returns:
    The current window size or -1 if its Infinite.
  - setWindowSize
```
public void setWindowSize(int windowSize)
                   throws MathIllegalArgumentException
```
    WindowSize controls the number of values that contribute to the reported statistics. For example, if windowSize is set to 3 and the values {1,2,3,4,5} have been added in that order then the available values are {3,4,5} and all reported statistics will be based on these values. If windowSize is decreased as a result of this call and there are more than the new value of elements in the current dataset, values from the front of the array are discarded to reduce the dataset to windowSize elements.
    
    Parameters:
    windowSize - sets the size of the window.
    
    Throws:
    
    MathIllegalArgumentException - if window size is less than 1 but not equal to INFINITE_WINDOW
  - getValues
```
public double[] getValues()
```
    Returns the current set of values in an array of double primitives. The order of addition is preserved. The returned array is a fresh copy of the underlying data -- i.e., it is not a reference to the stored data.
    
    Returns:
    returns the current set of numbers in the order in which they were added to this set
  - getSortedValues
```
public double[] getSortedValues()
```
    Returns the current set of values in an array of double primitives, sorted in ascending order. The returned array is a fresh copy of the underlying data -- i.e., it is not a reference to the stored data.
    
    Returns:
    returns the current set of numbers sorted in ascending order
  - getElement
```
public double getElement(int index)
```
    Returns the element at the specified index
    
    Parameters:
    index - The Index of the element
    
    Returns:
    return the element at the specified index
  - getPercentile
```
public double getPercentile(double p)
                     throws MathIllegalStateException,
                            MathIllegalArgumentException
```
    Returns an estimate for the pth percentile of the stored values.
    The implementation provided here follows the first estimation procedure presented here.
    Preconditions:
    - 0 < p ≤ 100 (otherwise an MathIllegalArgumentException is thrown)
    - at least one value must be stored (returns Double.NaN otherwise)
    Parameters:
    p - the requested percentile (scaled from 0 - 100)
    
    Returns:
    An estimate for the pth percentile of the stored data
    
    Throws:
    
    MathIllegalStateException - if percentile implementation has been overridden and the supplied implementation does not support setQuantile
    
    MathIllegalArgumentException - if p is not a valid quantile
  - toString
```
public String toString()
```
    Generates a text report displaying univariate statistics from values that have been added. Each statistic is displayed on a separate line.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    String with line feeds displaying statistics
  - apply
```
public double apply(UnivariateStatistic stat)
```
    Apply the given statistic to the data associated with this set of statistics.
    
    Parameters:
    stat - the statistic to apply
    
    Returns:
    the computed value of the statistic.
  - getMeanImpl
```
public UnivariateStatistic getMeanImpl()
```
    Returns the currently configured mean implementation.
    
    Returns:
    the UnivariateStatistic implementing the mean
    Since:
    
    1.2
  - setMeanImpl
```
public void setMeanImpl(UnivariateStatistic meanImpl)
```
    Sets the implementation for the mean.
    
    Parameters:
    meanImpl - the UnivariateStatistic instance to use for computing the mean
    Since:
    
    1.2
  - getGeometricMeanImpl
```
public UnivariateStatistic getGeometricMeanImpl()
```
    Returns the currently configured geometric mean implementation.
    
    Returns:
    the UnivariateStatistic implementing the geometric mean
    Since:
    
    1.2
  - setGeometricMeanImpl
```
public void setGeometricMeanImpl(UnivariateStatistic geometricMeanImpl)
```
    Sets the implementation for the gemoetric mean.
    
    Parameters:
    geometricMeanImpl - the UnivariateStatistic instance to use for computing the geometric mean
    Since:
    
    1.2
  - getKurtosisImpl
```
public UnivariateStatistic getKurtosisImpl()
```
    Returns the currently configured kurtosis implementation.
    
    Returns:
    the UnivariateStatistic implementing the kurtosis
    Since:
    
    1.2
  - setKurtosisImpl
```
public void setKurtosisImpl(UnivariateStatistic kurtosisImpl)
```
    Sets the implementation for the kurtosis.
    
    Parameters:
    kurtosisImpl - the UnivariateStatistic instance to use for computing the kurtosis
    Since:
    
    1.2
  - getMaxImpl
```
public UnivariateStatistic getMaxImpl()
```
    Returns the currently configured maximum implementation.
    
    Returns:
    the UnivariateStatistic implementing the maximum
    Since:
    
    1.2
  - setMaxImpl
```
public void setMaxImpl(UnivariateStatistic maxImpl)
```
    Sets the implementation for the maximum.
    
    Parameters:
    maxImpl - the UnivariateStatistic instance to use for computing the maximum
    Since:
    
    1.2
  - getMinImpl
```
public UnivariateStatistic getMinImpl()
```
    Returns the currently configured minimum implementation.
    
    Returns:
    the UnivariateStatistic implementing the minimum
    Since:
    
    1.2
  - setMinImpl
```
public void setMinImpl(UnivariateStatistic minImpl)
```
    Sets the implementation for the minimum.
    
    Parameters:
    minImpl - the UnivariateStatistic instance to use for computing the minimum
    Since:
    
    1.2
  - getPercentileImpl
```
public UnivariateStatistic getPercentileImpl()
```
    Returns the currently configured percentile implementation.
    
    Returns:
    the UnivariateStatistic implementing the percentile
    Since:
    
    1.2
  - setPercentileImpl
```
public void setPercentileImpl(UnivariateStatistic percentileImpl)
                       throws MathIllegalArgumentException
```
    Sets the implementation to be used by getPercentile(double). The supplied UnivariateStatistic must provide a setQuantile(double) method; otherwise IllegalArgumentException is thrown.
    
    Parameters:
    percentileImpl - the percentileImpl to set
    
    Throws:
    
    MathIllegalArgumentException - if the supplied implementation does not provide a setQuantile method
    Since:
    
    1.2
  - getSkewnessImpl
```
public UnivariateStatistic getSkewnessImpl()
```
    Returns the currently configured skewness implementation.
    
    Returns:
    the UnivariateStatistic implementing the skewness
    Since:
    
    1.2
  - setSkewnessImpl
```
public void setSkewnessImpl(UnivariateStatistic skewnessImpl)
```
    Sets the implementation for the skewness.
    
    Parameters:
    skewnessImpl - the UnivariateStatistic instance to use for computing the skewness
    Since:
    
    1.2
  - getVarianceImpl
```
public UnivariateStatistic getVarianceImpl()
```
    Returns the currently configured variance implementation.
    
    Returns:
    the UnivariateStatistic implementing the variance
    Since:
    
    1.2
  - setVarianceImpl
```
public void setVarianceImpl(UnivariateStatistic varianceImpl)
```
    Sets the implementation for the variance.
    
    Parameters:
    varianceImpl - the UnivariateStatistic instance to use for computing the variance
    Since:
    
    1.2
  - getSumsqImpl
```
public UnivariateStatistic getSumsqImpl()
```
    Returns the currently configured sum of squares implementation.
    
    Returns:
    the UnivariateStatistic implementing the sum of squares
    Since:
    
    1.2
  - setSumsqImpl
```
public void setSumsqImpl(UnivariateStatistic sumsqImpl)
```
    Sets the implementation for the sum of squares.
    
    Parameters:
    sumsqImpl - the UnivariateStatistic instance to use for computing the sum of squares
    Since:
    
    1.2
  - getSumImpl
```
public UnivariateStatistic getSumImpl()
```
    Returns the currently configured sum implementation.
    
    Returns:
    the UnivariateStatistic implementing the sum
    Since:
    
    1.2
  - setSumImpl
```
public void setSumImpl(UnivariateStatistic sumImpl)
```
    Sets the implementation for the sum.
    
    Parameters:
    sumImpl - the UnivariateStatistic instance to use for computing the sum
    Since:
    
    1.2
  - copy
```
public DescriptiveStatistics copy()
```
    Returns a copy of this DescriptiveStatistics instance with the same internal state.
    
    Returns:
    a copy of this
  - copy
```
public static void copy(DescriptiveStatistics source,
        DescriptiveStatistics dest)
                 throws NullArgumentException
```
    Copies source to dest.
    Neither source nor dest can be null.
    
    Parameters:
    source - DescriptiveStatistics to copy
    dest - DescriptiveStatistics to copy to
    
    Throws:
    
    NullArgumentException - if either source or dest is null

Class DescriptiveStatistics

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

INFINITE_WINDOW

windowSize

Constructor Detail

DescriptiveStatistics

DescriptiveStatistics

DescriptiveStatistics

DescriptiveStatistics

Method Detail

addValue

removeMostRecentValue

replaceMostRecentValue

getMean

getGeometricMean

getVariance

getPopulationVariance

getStandardDeviation

getQuadraticMean

getSkewness

getKurtosis

getMax

getMin

getN

getSum

getSumsq

clear

getWindowSize

setWindowSize

getValues

getSortedValues

getElement

getPercentile

toString

apply

getMeanImpl

setMeanImpl

getGeometricMeanImpl

setGeometricMeanImpl

getKurtosisImpl

setKurtosisImpl

getMaxImpl

setMaxImpl

getMinImpl

setMinImpl

getPercentileImpl

setPercentileImpl

getSkewnessImpl

setSkewnessImpl

getVarianceImpl

setVarianceImpl

getSumsqImpl

setSumsqImpl

getSumImpl

setSumImpl

copy

copy