org.hipparchus.stat.descriptive

Class MultivariateSummaryStatistics

• java.lang.Object
• org.hipparchus.stat.descriptive.MultivariateSummaryStatistics
• All Implemented Interfaces:
Serializable, StatisticalMultivariateSummary

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.

To compute statistics for a stream of n-tuples, construct a MultivariateSummaryStatistics 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 ith array element is the value of the given statistic for data range consisting of the ith 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.

Serialized Form
• Constructor Summary

Constructors
Constructor and Description
MultivariateSummaryStatistics(int dimension)
Construct a MultivariateSummaryStatistics instance for the given dimension.
MultivariateSummaryStatistics(int dimension, boolean covarianceBiasCorrection)
Construct a MultivariateSummaryStatistics instance for the given dimension.
• Method Summary

All 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 of the available values.
int getDimension()
Returns the dimension of the data
double[] getGeometricMean()
Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that correspond to each multivariate sample
double[] getMax()
Returns an array whose ith entry is the maximum of the ith entries of the arrays that correspond to each multivariate sample
double[] getMean()
Returns an array whose ith entry is the mean of the ith entries of the arrays that correspond to each multivariate sample
double[] getMin()
Returns an array whose ith entry is the minimum of the ith entries of the arrays that correspond to each multivariate sample
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 correspond to each multivariate sample
double[] getSumLog()
Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that correspond to each multivariate sample
double[] getSumSq()
Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that correspond to each multivariate sample
int hashCode()
Returns hash code based on values of statistics
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 dimension)
Construct a MultivariateSummaryStatistics instance for the given dimension. The returned instance will compute the unbiased sample covariance.

The returned instance is not thread-safe.

Parameters:
dimension - dimension of the data
• MultivariateSummaryStatistics

public MultivariateSummaryStatistics(int dimension,
boolean covarianceBiasCorrection)
Construct a MultivariateSummaryStatistics instance for the given dimension.

The returned instance is not thread-safe.

Parameters:
dimension - dimension of the data
covarianceBiasCorrection - if true, the returned instance will compute the unbiased sample covariance, otherwise the population covariance
• Method Detail

public void addValue(double[] value)
throws MathIllegalArgumentException
Add an n-tuple to the data
Parameters:
value - the n-tuple to add
Throws:
MathIllegalArgumentException - if the array is null or the length of the array does not match the one used at construction
• clear

public void clear()
Resets all statistics and storage.
• 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 ith entry is the sum of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getSum in interface StatisticalMultivariateSummary
Returns:
the array of component sums
• getSumSq

public double[] getSumSq()
Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getSumSq in interface StatisticalMultivariateSummary
Returns:
the array of component sums of squares
• getSumLog

public double[] getSumLog()
Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getSumLog in interface StatisticalMultivariateSummary
Returns:
the array of component log sums
• getMean

public double[] getMean()
Returns an array whose ith entry is the mean of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getMean in interface StatisticalMultivariateSummary
Returns:
the array of component means
• getCovariance

public RealMatrix getCovariance()
Returns the covariance of the available values.
Specified by:
getCovariance in interface StatisticalMultivariateSummary
Returns:
The covariance, null if no multivariate sample have been added or a zeroed matrix for a single value set.
• getMax

public double[] getMax()
Returns an array whose ith entry is the maximum of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getMax in interface StatisticalMultivariateSummary
Returns:
the array of component maxima
• getMin

public double[] getMin()
Returns an array whose ith entry is the minimum of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getMin in interface StatisticalMultivariateSummary
Returns:
the array of component minima
• getGeometricMean

public double[] getGeometricMean()
Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that correspond to each multivariate sample
Specified by:
getGeometricMean in interface StatisticalMultivariateSummary
Returns:
the array of component geometric means
• getStandardDeviation

public 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[])
Specified by:
getStandardDeviation in interface StatisticalMultivariateSummary
Returns:
the array of component standard deviations
• 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
• 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