MultivariateSummaryStatistics (Apache Commons Math 3.6.1 API)

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

All Implemented Interfaces:

Serializable, StatisticalMultivariateSummary

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

See Also:
Serialized Form

Constructor Summary

Constructors
Constructor and Description
`MultivariateSummaryStatistics(int k, 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 i^th entry is the geometric mean of the i^th entries of the arrays that have been added using `addValue(double[])`
`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[])`
`StorelessUnivariateStatistic[]`	`getMaxImpl()` Returns the currently configured maximum implementation
`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[])`
`StorelessUnivariateStatistic[]`	`getMeanImpl()` Returns the currently configured mean implementation
`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[])`
`StorelessUnivariateStatistic[]`	`getMinImpl()` Returns the currently configured minimum implementation
`long`	`getN()` Returns the number of available values
`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[])`
`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[])`
`StorelessUnivariateStatistic[]`	`getSumImpl()` Returns the currently configured Sum implementation
`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[])`
`StorelessUnivariateStatistic[]`	`getSumLogImpl()` Returns the currently configured sum of logs implementation
`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[])`
`StorelessUnivariateStatistic[]`	`getSumsqImpl()` Returns the currently configured sum of squares implementation
`int`	`hashCode()` Returns hash code based on values of statistics
`void`	`setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImpl)` Sets the implementation for the geometric mean.
`void`	`setMaxImpl(StorelessUnivariateStatistic[] maxImpl)` Sets the implementation for the maximum.
`void`	`setMeanImpl(StorelessUnivariateStatistic[] meanImpl)` Sets the implementation for the mean.
`void`	`setMinImpl(StorelessUnivariateStatistic[] minImpl)` Sets the implementation for the minimum.
`void`	`setSumImpl(StorelessUnivariateStatistic[] sumImpl)` Sets the implementation for the Sum.
`void`	`setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl)` 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 k,
                             boolean isCovarianceBiasCorrected)
```
    Construct a MultivariateSummaryStatistics instance
    
    Parameters:
    k - 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)
              throws DimensionMismatchException
```
    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[] sumImpl)
                throws MathIllegalStateException,
                       DimensionMismatchException
```
    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:
    sumImpl - 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)
                  throws MathIllegalStateException,
                         DimensionMismatchException
```
    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[] minImpl)
                throws MathIllegalStateException,
                       DimensionMismatchException
```
    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:
    minImpl - 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[] maxImpl)
                throws MathIllegalStateException,
                       DimensionMismatchException
```
    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:
    maxImpl - 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[] sumLogImpl)
                   throws MathIllegalStateException,
                          DimensionMismatchException
```
    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:
    sumLogImpl - 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[] geoMeanImpl)
                    throws MathIllegalStateException,
                           DimensionMismatchException
```
    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:
    geoMeanImpl - 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[] meanImpl)
                 throws MathIllegalStateException,
                        DimensionMismatchException
```
    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:
    meanImpl - 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)

Class MultivariateSummaryStatistics

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

MultivariateSummaryStatistics

Method Detail

addValue

getDimension

getN

getSum

getSumSq

getSumLog

getMean

getStandardDeviation

getCovariance

getMax

getMin

getGeometricMean

toString

clear

equals

hashCode

getSumImpl

setSumImpl

getSumsqImpl

setSumsqImpl

getMinImpl

setMinImpl

getMaxImpl

setMaxImpl

getSumLogImpl

setSumLogImpl

getGeoMeanImpl

setGeoMeanImpl

getMeanImpl

setMeanImpl