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 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.

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor	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 Instance Methods Concrete Methods
Modifier and Type	Method	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 i^th entry is the geometric mean of the i^th entries of the arrays that correspond to each multivariate sample
`double[]`	`getMax()`	Returns an array whose i^th entry is the maximum of the i^th entries of the arrays that correspond to each multivariate sample
`double[]`	`getMean()`	Returns an array whose i^th entry is the mean of the i^th entries of the arrays that correspond to each multivariate sample
`double[]`	`getMin()`	Returns an array whose i^th entry is the minimum of the i^th entries of the arrays that correspond to each multivariate sample
`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 correspond to each multivariate sample
`double[]`	`getSumLog()`	Returns an array whose i^th entry is the sum of logs of the i^th entries of the arrays that correspond to each multivariate sample
`double[]`	`getSumSq()`	Returns an array whose i^th entry is the sum of squares of the i^th 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
  - addValue
```
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 i^th entry is the sum of the i^th 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 i^th entry is the sum of squares of the i^th 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 i^th entry is the sum of logs of the i^th 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 i^th entry is the mean of the i^th 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 i^th entry is the maximum of the i^th 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 i^th entry is the minimum of the i^th 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 i^th entry is the geometric mean of the i^th 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 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
  - 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

Class MultivariateSummaryStatistics

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

MultivariateSummaryStatistics

MultivariateSummaryStatistics

Method Detail

addValue

clear

getDimension

getN

getSum

getSumSq

getSumLog

getMean

getCovariance

getMax

getMin

getGeometricMean

getStandardDeviation

toString

equals

hashCode