fr.cnes.sirius.patrius.math.stat.descriptive

Class MultivariateSummaryStatistics

java.lang.Object

fr.cnes.sirius.patrius.math.stat.descriptive.MultivariateSummaryStatistics

All Implemented Interfaces:

StatisticalMultivariateSummary, Serializable

Direct Known Subclasses:

SynchronizedMultivariateSummaryStatistics

public class MultivariateSummaryStatistics
extends Object
implements StatisticalMultivariateSummary, Serializable

Computes summary statistics for a stream of n-tuples added using the addValue method. The data values are not stored in memory, so this class can be used to compute statistics for very large n-tuple streams.

The StorelessUnivariateStatistic instances used to maintain summary state and compute statistics are configurable via setters. For example, the default implementation for the mean can be overridden by calling setMeanImpl(StorelessUnivariateStatistic[]). Actual parameters to these methods must implement the StorelessUnivariateStatistic interface and configuration must be completed before addValue is called. No configuration is necessary to use the default, commons-math provided implementations.

To compute statistics for a stream of n-tuples, construct a MultivariateStatistics instance with dimension n and then use addValue(double[]) to add n-tuples. The getXxx methods where Xxx is a statistic return an array of double values, where for i = 0,...,n-1 the i^th array element is the value of the given statistic for data range consisting of the i^th element of each of the input n-tuples. For example, if addValue is called with actual parameters {0, 1, 2}, then {3, 4, 5} and finally {6, 7, 8}, getSum will return a three-element array with values {0+3+6, 1+4+7, 2+5+8}

Note: This class is not thread-safe. Use SynchronizedMultivariateSummaryStatistics if concurrent access from multiple threads is required.

Since:

1.2

Version:

$Id: MultivariateSummaryStatistics.java 18108 2017-10-04 06:45:27Z bignon $

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MultivariateSummaryStatistics(int kIn, boolean isCovarianceBiasCorrected) Construct a MultivariateSummaryStatistics instance

Method Summary

Methods

Modifier and Type	Method and Description
void	addValue(double[] value) Add an n-tuple to the data
void	clear() Resets all statistics and storage
boolean	equals(Object object) Returns true iff object is a MultivariateSummaryStatistics instance and all statistics have the same values as this.
RealMatrix	getCovariance() Returns the covariance matrix of the values that have been added.
int	getDimension() Returns the dimension of the data
StorelessUnivariateStatistic[]	getGeoMeanImpl() Returns the currently configured geometric mean implementation
double[]	getGeometricMean() Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that have been added using addValue(double[])
double[]	getMax() Returns an array whose ith entry is the maximum of the ith entries of the arrays that have been added using addValue(double[])
StorelessUnivariateStatistic[]	getMaxImpl() Returns the currently configured maximum implementation
double[]	getMean() Returns an array whose ith entry is the mean of the ith entries of the arrays that have been added using addValue(double[])
StorelessUnivariateStatistic[]	getMeanImpl() Returns the currently configured mean implementation
double[]	getMin() Returns an array whose ith entry is the minimum of the ith entries of the arrays that have been added using addValue(double[])
StorelessUnivariateStatistic[]	getMinImpl() Returns the currently configured minimum implementation
long	getN() Returns the number of available values
double[]	getStandardDeviation() Returns an array whose ith entry is the standard deviation of the ith entries of the arrays that have been added using addValue(double[])
double[]	getSum() Returns an array whose ith entry is the sum of the ith entries of the arrays that have been added using addValue(double[])
StorelessUnivariateStatistic[]	getSumImpl() Returns the currently configured Sum implementation
double[]	getSumLog() Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that have been added using addValue(double[])
StorelessUnivariateStatistic[]	getSumLogImpl() Returns the currently configured sum of logs implementation
double[]	getSumSq() Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that have been added using addValue(double[])
StorelessUnivariateStatistic[]	getSumsqImpl() Returns the currently configured sum of squares implementation
int	hashCode() Returns hash code based on values of statistics
void	setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImplIn) Sets the implementation for the geometric mean.
void	setMaxImpl(StorelessUnivariateStatistic[] maxImplIn) Sets the implementation for the maximum.
void	setMeanImpl(StorelessUnivariateStatistic[] meanImplIn) Sets the implementation for the mean.
void	setMinImpl(StorelessUnivariateStatistic[] minImplIn) Sets the implementation for the minimum.
void	setSumImpl(StorelessUnivariateStatistic[] sumImplIn) Sets the implementation for the Sum.
void	setSumLogImpl(StorelessUnivariateStatistic[] sumLogImplIn) Sets the implementation for the sum of logs.
void	setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl) Sets the implementation for the sum of squares.
String	toString() Generates a text report displaying summary statistics from values that have been added.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

MultivariateSummaryStatistics

public MultivariateSummaryStatistics(int kIn,
                             boolean isCovarianceBiasCorrected)

Construct a MultivariateSummaryStatistics instance

Parameters:

kIn - dimension of the data

isCovarianceBiasCorrected - if true, the unbiased sample covariance is computed, otherwise the biased population covariance is computed

Method Detail

addValue

public void addValue(double[] value)

Add an n-tuple to the data

Parameters:

value - the n-tuple to add

Throws:

DimensionMismatchException - if the length of the array does not match the one used at construction

getDimension

public int getDimension()

Returns the dimension of the data

Specified by:

getDimension in interface StatisticalMultivariateSummary

Returns:

The dimension of the data

getN

public long getN()

Returns the number of available values

Specified by:

getN in interface StatisticalMultivariateSummary

Returns:

The number of available values

getSum

public double[] getSum()

Returns an array whose i^th entry is the sum of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getSum in interface StatisticalMultivariateSummary

Returns:

the array of component sums

getSumSq

public double[] getSumSq()

Returns an array whose i^th entry is the sum of squares of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getSumSq in interface StatisticalMultivariateSummary

Returns:

the array of component sums of squares

getSumLog

public double[] getSumLog()

Returns an array whose i^th entry is the sum of logs of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getSumLog in interface StatisticalMultivariateSummary

Returns:

the array of component log sums

getMean

public double[] getMean()

Returns an array whose i^th entry is the mean of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getMean in interface StatisticalMultivariateSummary

Returns:

the array of component means

getStandardDeviation

public double[] getStandardDeviation()

Returns an array whose i^th entry is the standard deviation of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getStandardDeviation in interface StatisticalMultivariateSummary

Returns:

the array of component standard deviations

getCovariance

public RealMatrix getCovariance()

Returns the covariance matrix of the values that have been added.

Specified by:

getCovariance in interface StatisticalMultivariateSummary

Returns:

the covariance matrix

getMax

public double[] getMax()

Returns an array whose i^th entry is the maximum of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getMax in interface StatisticalMultivariateSummary

Returns:

the array of component maxima

getMin

public double[] getMin()

Returns an array whose i^th entry is the minimum of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getMin in interface StatisticalMultivariateSummary

Returns:

the array of component minima

getGeometricMean

public double[] getGeometricMean()

Returns an array whose i^th entry is the geometric mean of the i^th entries of the arrays that have been added using addValue(double[])

Specified by:

getGeometricMean in interface StatisticalMultivariateSummary

Returns:

the array of component geometric means

toString

public String toString()

Generates a text report displaying summary statistics from values that have been added.

Overrides:

toString in class Object

Returns:

String with line feeds displaying statistics

clear

public void clear()

Resets all statistics and storage

equals

public boolean equals(Object object)

Returns true iff object is a MultivariateSummaryStatistics instance and all statistics have the same values as this.

Overrides:

equals in class Object

Parameters:

object - the object to test equality against.

Returns:

true if object equals this

hashCode

public int hashCode()

Returns hash code based on values of statistics

Overrides:

hashCode in class Object

Returns:

hash code

getSumImpl

public StorelessUnivariateStatistic[] getSumImpl()

Returns the currently configured Sum implementation

Returns:

the StorelessUnivariateStatistic implementing the sum

setSumImpl

public void setSumImpl(StorelessUnivariateStatistic[] sumImplIn)

Sets the implementation for the Sum.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

sumImplIn - the StorelessUnivariateStatistic instance to use for computing the Sum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)

getSumsqImpl

public StorelessUnivariateStatistic[] getSumsqImpl()

Returns the currently configured sum of squares implementation

Returns:

the StorelessUnivariateStatistic implementing the sum of squares

setSumsqImpl

public void setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl)

Sets the implementation for the sum of squares.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

sumsqImpl - the StorelessUnivariateStatistic instance to use for computing the sum of squares

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)

getMinImpl

public StorelessUnivariateStatistic[] getMinImpl()

Returns the currently configured minimum implementation

Returns:

the StorelessUnivariateStatistic implementing the minimum

setMinImpl

public void setMinImpl(StorelessUnivariateStatistic[] minImplIn)

Sets the implementation for the minimum.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

minImplIn - the StorelessUnivariateStatistic instance to use for computing the minimum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)

getMaxImpl

public StorelessUnivariateStatistic[] getMaxImpl()

Returns the currently configured maximum implementation

Returns:

the StorelessUnivariateStatistic implementing the maximum

setMaxImpl

public void setMaxImpl(StorelessUnivariateStatistic[] maxImplIn)

Sets the implementation for the maximum.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

maxImplIn - the StorelessUnivariateStatistic instance to use for computing the maximum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)

getSumLogImpl

public StorelessUnivariateStatistic[] getSumLogImpl()

Returns the currently configured sum of logs implementation

Returns:

the StorelessUnivariateStatistic implementing the log sum

setSumLogImpl

public void setSumLogImpl(StorelessUnivariateStatistic[] sumLogImplIn)

Sets the implementation for the sum of logs.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

sumLogImplIn - the StorelessUnivariateStatistic instance to use for computing the log sum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)

getGeoMeanImpl

public StorelessUnivariateStatistic[] getGeoMeanImpl()

Returns the currently configured geometric mean implementation

Returns:

the StorelessUnivariateStatistic implementing the geometric mean

setGeoMeanImpl

public void setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImplIn)

Sets the implementation for the geometric mean.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

geoMeanImplIn - the StorelessUnivariateStatistic instance to use for computing the geometric mean

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)

getMeanImpl

public StorelessUnivariateStatistic[] getMeanImpl()

Returns the currently configured mean implementation

Returns:

the StorelessUnivariateStatistic implementing the mean

setMeanImpl

public void setMeanImpl(StorelessUnivariateStatistic[] meanImplIn)

Sets the implementation for the mean.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Parameters:

meanImplIn - the StorelessUnivariateStatistic instance to use for computing the mean

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

MathIllegalStateException - if data has already been added (i.e if n > 0)