Package org.apache.commons.math.stat.descriptive.moment

Class Mean

  • All Implemented Interfaces:
    java.io.Serializable, StorelessUnivariateStatistic, UnivariateStatistic, WeightedEvaluation
    public class Mean
extends AbstractStorelessUnivariateStatistic
implements java.io.Serializable, WeightedEvaluation

    Computes the arithmetic mean of a set of values. Uses the definitional formula:

    mean = sum(x_i) / n

    where n is the number of observations.

    When increment(double) is used to add data incrementally from a stream of (unstored) values, the value of the statistic that getResult() returns is computed using the following recursive updating algorithm:

    1. Initialize m = the first value
    2. For each additional value, update using
      m = m + (new value - m) / (number of observations)

    If AbstractStorelessUnivariateStatistic.evaluate(double[]) is used to compute the mean of an array of stored values, a two-pass, corrected algorithm is used, starting with the definitional formula computed using the array of stored values and then correcting this by adding the mean deviation of the data values from the arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing Sample Means and Variances," Robert F. Ling, Journal of the American Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866.

    Returns Double.NaN if the dataset is empty.

    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:
    Serialized Form

    • Constructor Summary

      Constructors 
      Constructor Description
      Mean()
      Constructs a Mean.
      Mean​(FirstMoment m1)
      Constructs a Mean with an External Moment.
      Mean​(Mean original)
      Copy constructor, creates a new Mean identical to the original

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void clear()
      Clears the internal state of the Statistic
      Mean copy()
      Returns a copy of the statistic with the same internal state.
      static void copy​(Mean source, Mean dest)
      Copies source to dest.
      double evaluate​(double[] values, double[] weights)
      Returns the weighted arithmetic mean of the entries in the input array.
      double evaluate​(double[] values, double[] weights, int begin, int length)
      Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
      double evaluate​(double[] values, int begin, int length)
      Returns the arithmetic mean 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.

      • Methods inherited from class java.lang.Object

        getClass, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • Mean

        public Mean()
        Constructs a Mean.

      • Mean

        public Mean​(FirstMoment m1)
        Constructs a Mean with an External Moment.
        Parameters:
        m1 - the moment

      • Mean

        public Mean​(Mean original)
        Copy constructor, creates a new Mean identical to the original
        Parameters:
        original - the Mean instance to copy

    • Method Detail

      • getN

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

      • evaluate

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

        Throws IllegalArgumentException if the array is null.

        See Mean for details on the computing algorithm.

        Specified by:
        evaluate in interface UnivariateStatistic
        Overrides:
        evaluate in class AbstractStorelessUnivariateStatistic
        Parameters:
        values - the input array
        begin - index of the first array element to include
        length - the number of elements to include
        Returns:
        the mean of the values or Double.NaN if length = 0
        Throws:
        java.lang.IllegalArgumentException - if the array is null or the array index parameters are not valid
        See Also:
        UnivariateStatistic.evaluate(double[], int, int)

      • evaluate

        public double evaluate​(double[] values,
                       double[] weights,
                       int begin,
                       int length)
        Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

        Throws IllegalArgumentException if either array is null.

        See Mean for details on the computing algorithm. The two-pass algorithm described above is used here, with weights applied in computing both the original estimate and the correction factor.

        Throws IllegalArgumentException if any of the following are true:

        • the values array is null
        • the weights array is null
        • the weights array does not have the same length as the values array
        • the weights array contains one or more infinite values
        • the weights array contains one or more NaN values
        • the weights array contains negative values
        • the start and length arguments do not determine a valid array

        Specified by:
        evaluate in interface WeightedEvaluation
        Parameters:
        values - the input array
        weights - the weights array
        begin - index of the first array element to include
        length - the number of elements to include
        Returns:
        the mean of the values or Double.NaN if length = 0
        Throws:
        java.lang.IllegalArgumentException - if the parameters are not valid
        Since:
        2.1

      • evaluate

        public double evaluate​(double[] values,
                       double[] weights)
        Returns the weighted arithmetic mean of the entries in the input array.

        Throws IllegalArgumentException if either array is null.

        See Mean for details on the computing algorithm. The two-pass algorithm described above is used here, with weights applied in computing both the original estimate and the correction factor.

        Throws IllegalArgumentException if any of the following are true:

        • the values array is null
        • the weights array is null
        • the weights array does not have the same length as the values array
        • the weights array contains one or more infinite values
        • the weights array contains one or more NaN values
        • the weights array contains negative values

        Specified by:
        evaluate in interface WeightedEvaluation
        Parameters:
        values - the input array
        weights - the weights array
        Returns:
        the mean of the values or Double.NaN if length = 0
        Throws:
        java.lang.IllegalArgumentException - if the parameters are not valid
        Since:
        2.1

      • copy

        public static void copy​(Mean source,
                        Mean dest)
        Copies source to dest.

        Neither source nor dest can be null.

        Parameters:
        source - Mean to copy
        dest - Mean to copy to
        Throws:
        java.lang.NullPointerException - if either source or dest is null