Package org.hipparchus.stat.descriptive.moment

Class StandardDeviation

java.lang.Object
org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic
org.hipparchus.stat.descriptive.moment.StandardDeviation
All Implemented Interfaces:
Serializable, DoubleConsumer, StorelessUnivariateStatistic, UnivariateStatistic, MathArrays.Function
public class StandardDeviation extends AbstractStorelessUnivariateStatistic implements Serializable
Computes the sample standard deviation.

The standard deviation is the positive square root of the variance. This implementation wraps a Variance instance.

The isBiasCorrected property of the wrapped Variance instance is exposed, so that this class can be used to compute both the "sample standard deviation" (the square root of the bias-corrected "sample variance") or the "population standard deviation" (the square root of the non-bias-corrected "population variance"). See Variance for more information.

Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the increment() or clear() method, it must be synchronized externally.

See Also:

  • Constructor Summary

    Constructors
    Constructor
    Description
    StandardDeviation()
    Constructs a StandardDeviation.
    StandardDeviation(boolean isBiasCorrected)
    Constructs a StandardDeviation with the specified value for the isBiasCorrected property.
    StandardDeviation(boolean isBiasCorrected, SecondMoment m2)
    Constructs a StandardDeviation with the specified value for the isBiasCorrected property and the supplied external moment.
    StandardDeviation(SecondMoment m2)
    Constructs a StandardDeviation from an external second moment.
    StandardDeviation(StandardDeviation original)
    Copy constructor, creates a new StandardDeviation identical to the original.

  • Method Summary

    Modifier and Type
    Method
    Description
    void
    clear()
    Clears the internal state of the Statistic
    StandardDeviation
    copy()
    Returns a copy of the statistic with the same internal state.
    double
    evaluate(double[] values, double mean)
    Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
    double
    evaluate(double[] values, double mean, int begin, int length)
    Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
    double
    evaluate(double[] values, int begin, int length)
    Returns the Standard Deviation of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
    long
    getN()
    Returns the number of values that have been added.
    double
    getResult()
    Returns the current value of the Statistic.
    void
    increment(double d)
    Updates the internal state of the statistic to reflect the addition of the new value.
    boolean
    isBiasCorrected()
    Check if bias is corrected.
    StandardDeviation
    withBiasCorrection(boolean biasCorrection)
    Returns a new copy of this standard deviation with the given bias correction setting.

    Methods inherited from class org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic

    equals, hashCode, toString

    Methods inherited from class java.lang.Object

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

    Methods inherited from interface java.util.function.DoubleConsumer

    andThen

    Methods inherited from interface org.hipparchus.stat.descriptive.StorelessUnivariateStatistic

    accept, incrementAll, incrementAll

    Methods inherited from interface org.hipparchus.stat.descriptive.UnivariateStatistic

    evaluate

  • Constructor Details

    • StandardDeviation

      public StandardDeviation()
      Constructs a StandardDeviation. Sets the underlying Variance instance's isBiasCorrected property to true.

    • StandardDeviation

      public StandardDeviation(SecondMoment m2)
      Constructs a StandardDeviation from an external second moment.
      Parameters:
      m2 - the external moment

    • StandardDeviation

      public StandardDeviation(boolean isBiasCorrected)
      Constructs a StandardDeviation with the specified value for the isBiasCorrected property. If this property is set to true, the Variance used in computing results will use the bias-corrected, or "sample" formula. See Variance for details.
      Parameters:
      isBiasCorrected - whether or not the variance computation will use the bias-corrected formula

    • StandardDeviation

      public StandardDeviation(boolean isBiasCorrected, SecondMoment m2)
      Constructs a StandardDeviation with the specified value for the isBiasCorrected property and the supplied external moment. If isBiasCorrected is set to true, the Variance used in computing results will use the bias-corrected, or "sample" formula. See Variance for details.
      Parameters:
      isBiasCorrected - whether or not the variance computation will use the bias-corrected formula
      m2 - the external moment

    • StandardDeviation

      public StandardDeviation(StandardDeviation original) throws NullArgumentException
      Copy constructor, creates a new StandardDeviation identical to the original.
      Parameters:
      original - the StandardDeviation instance to copy
      Throws:
      NullArgumentException - if original is null

  • Method Details

    • increment

      public void increment(double d)
      Updates the internal state of the statistic to reflect the addition of the new value.
      Specified by:
      increment in interface StorelessUnivariateStatistic
      Specified by:
      increment in class AbstractStorelessUnivariateStatistic
      Parameters:
      d - the new value.

    • getN

      public long getN()
      Returns the number of values that have been added.
      Specified by:
      getN in interface StorelessUnivariateStatistic
      Returns:
      the number of values.

    • getResult

      public double getResult()
      Returns the current value of the Statistic.
      Specified by:
      getResult in interface StorelessUnivariateStatistic
      Specified by:
      getResult in class AbstractStorelessUnivariateStatistic
      Returns:
      value of the statistic, Double.NaN if it has been cleared or just instantiated.

    • clear

      public void clear()
      Clears the internal state of the Statistic
      Specified by:
      clear in interface StorelessUnivariateStatistic
      Specified by:
      clear in class AbstractStorelessUnivariateStatistic

    • evaluate

      public double evaluate(double[] values, int begin, int length) throws MathIllegalArgumentException
      Returns the Standard Deviation of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

      Returns 0 for a single-value (i.e. length = 1) sample.

      Does not change the internal state of the statistic.

      Specified by:
      evaluate in interface MathArrays.Function
      Specified by:
      evaluate in interface StorelessUnivariateStatistic
      Specified by:
      evaluate in interface UnivariateStatistic
      Parameters:
      values - the input array
      begin - index of the first array element to include
      length - the number of elements to include
      Returns:
      the standard deviation of the values or Double.NaN if length = 0
      Throws:
      MathIllegalArgumentException - if the array is null or the array index parameters are not valid
      See Also:

    • evaluate

      public double evaluate(double[] values, double mean, int begin, int length) throws MathIllegalArgumentException
      Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value. Returns Double.NaN if the designated subarray is empty.

      Returns 0 for a single-value (i.e. length = 1) sample.

      The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.

      Does not change the internal state of the statistic.

      Parameters:
      values - the input array
      mean - the precomputed mean value
      begin - index of the first array element to include
      length - the number of elements to include
      Returns:
      the standard deviation of the values or Double.NaN if length = 0
      Throws:
      MathIllegalArgumentException - if the array is null or the array index parameters are not valid

    • evaluate

      public double evaluate(double[] values, double mean) throws MathIllegalArgumentException
      Returns the Standard Deviation of the entries in the input array, using the precomputed mean value. Returns Double.NaN if the designated subarray is empty.

      Returns 0 for a single-value (i.e. length = 1) sample.

      The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.

      Does not change the internal state of the statistic.

      Parameters:
      values - the input array
      mean - the precomputed mean value
      Returns:
      the standard deviation of the values or Double.NaN if length = 0
      Throws:
      MathIllegalArgumentException - if the array is null

    • isBiasCorrected

      public boolean isBiasCorrected()
      Check if bias is corrected.
      Returns:
      Returns the isBiasCorrected.

    • withBiasCorrection

      public StandardDeviation withBiasCorrection(boolean biasCorrection)
      Returns a new copy of this standard deviation with the given bias correction setting.
      Parameters:
      biasCorrection - The bias correction flag to set.
      Returns:
      a copy of this instance with the given bias correction setting

    • copy

      public StandardDeviation copy()
      Returns a copy of the statistic with the same internal state.
      Specified by:
      copy in interface StorelessUnivariateStatistic
      Specified by:
      copy in interface UnivariateStatistic
      Specified by:
      copy in class AbstractStorelessUnivariateStatistic
      Returns:
      a copy of the statistic