Package pal.statistics

Class DiscreteStatistics

  • public class DiscreteStatistics
extends java.lang.Object
    simple discrete statistics (mean, variance, cumulative probability, quantiles etc.)
    Version:
    $Id: DiscreteStatistics.java,v 1.5 2001/07/13 14:39:13 korbinian Exp $
    Author:
    Korbinian Strimmer

    • Method Summary

      All Methods Static Methods Concrete Methods 
      Modifier and Type Method Description
      static double cdf​(double z, double[] x)
      compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
      static double cdf​(double z, double[] x, int[] indices)
      compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
      static double mean​(double[] x)
      compute mean
      static double quantile​(double q, double[] x)
      compute the q-th quantile for a distribution of x (= inverse cdf)
      static double quantile​(double q, double[] x, int[] indices)
      compute the q-th quantile for a distribution of x (= inverse cdf)
      static double skewness​(double[] x)
      compute fisher skewness
      static double stdev​(double[] x)
      compute standard deviation
      static double variance​(double[] x)
      compute variance (ML estimator)
      static double variance​(double[] x, double mean)
      compute variance (ML estimator)
      static double varianceSampleMean​(double[] x)
      compute variance of sample mean (ML estimator)
      static double varianceSampleMean​(double[] x, double mean)
      compute variance of sample mean (ML estimator)

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • DiscreteStatistics

        public DiscreteStatistics()

    • Method Detail

      • mean

        public static double mean​(double[] x)
        compute mean
        Parameters:
        x - list of numbers
        Returns:
        mean

      • variance

        public static double variance​(double[] x,
                              double mean)
        compute variance (ML estimator)
        Parameters:
        x - list of numbers
        mean - assumed mean of x
        Returns:
        variance of x (ML estimator)

      • skewness

        public static double skewness​(double[] x)
        compute fisher skewness
        Parameters:
        x - list of numbers
        Returns:
        skewness of x

      • stdev

        public static double stdev​(double[] x)
        compute standard deviation
        Parameters:
        x - list of numbers
        Returns:
        standard deviation of x

      • variance

        public static double variance​(double[] x)
        compute variance (ML estimator)
        Parameters:
        x - list of numbers
        Returns:
        variance of x (ML estimator)

      • varianceSampleMean

        public static double varianceSampleMean​(double[] x,
                                        double mean)
        compute variance of sample mean (ML estimator)
        Parameters:
        x - list of numbers
        mean - assumed mean of x
        Returns:
        variance of x (ML estimator)

      • varianceSampleMean

        public static double varianceSampleMean​(double[] x)
        compute variance of sample mean (ML estimator)
        Parameters:
        x - list of numbers
        Returns:
        variance of x (ML estimator)

      • quantile

        public static double quantile​(double q,
                              double[] x,
                              int[] indices)
        compute the q-th quantile for a distribution of x (= inverse cdf)
        Parameters:
        q - quantile (0 < q <= 1)
        x - discrete distribution (an unordered list of numbers)
        indices - index sorting x
        Returns:
        q-th quantile

      • quantile

        public static double quantile​(double q,
                              double[] x)
        compute the q-th quantile for a distribution of x (= inverse cdf)
        Parameters:
        q - quantile (0 <= q <= 1)
        x - discrete distribution (an unordered list of numbers)
        Returns:
        q-th quantile

      • cdf

        public static double cdf​(double z,
                         double[] x,
                         int[] indices)
        compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
        Parameters:
        z - threshold value
        x - discrete distribution (an unordered list of numbers)
        indices - index sorting x
        Returns:
        cumulative probability

      • cdf

        public static double cdf​(double z,
                         double[] x)
        compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
        Parameters:
        z - threshold value
        x - discrete distribution (an unordered list of numbers)
        Returns:
        cumulative probability