org.apache.commons.math3.stat.descriptive

## Class MultivariateSummaryStatistics

- 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 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. Use `SynchronizedMultivariateSummaryStatistics` if concurrent access from multiple threads is required.

  Since:
    1.2
  Version:
    $Id: MultivariateSummaryStatistics.java 1416643 2012-12-03 19:37:14Z tn $
  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 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[] 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 ith entry is the sum of the ith 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 ith entry is the sum of squares of the ith 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 ith entry is the sum of logs of the ith 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 ith entry is the mean of the ith 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 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

    - #### 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 ith entry is the maximum of the ith 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 ith entry is the minimum of the ith 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 ith entry is the geometric mean of the ith 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)

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