Package ffx.numerics.math

Class BootStrapStatistics

java.lang.Object
ffx.numerics.math.BootStrapStatistics
public class BootStrapStatistics extends Object
The BootStrapStatistics class uses bootstrapping to estimate statistics from a given population.
Since:
1.0
Author:
Michael J. Schnieders, Rose Gogal

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    final long
    count
    The number of entries.
    final long
    dof
    The number of degrees of freedom.
    final double
    max
    The maximum value.
    final double
    mean
    The mean value.
    final double
    min
    The minimum value.
    final double
    sd
    The standard deviation.
    final double
    sdPopulation
    The population standard deviation.
    final double
    sum
    The sum of all values.
    final double
    sumWeights
    The sum of all weights.
    final double
    var
    The variance.
    final double
    varPopulation
    The population variance.

  • Constructor Summary

    Constructors
    Constructor
    Description
    BootStrapStatistics(double[] values)
    Constructs a static summary of a statistic from provided values.
    BootStrapStatistics(double[] values, double[] weights, int first, int last, int stride)
    Constructs a static summary of a statistic from provided values.
    BootStrapStatistics(double[] values, int first)
    Constructs a static summary of a statistic from provided values.
    BootStrapStatistics(double[] values, int first, int last)
    Constructs a static summary of a statistic from provided values.
    BootStrapStatistics(double[] values, int first, int last, int stride)
    Constructs a static summary of a statistic from provided values.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    confidenceInterval()
    Computes a 95% confidence interval based on a Student's T-distribution.
    double
    confidenceInterval(double alpha)
    Computes a confidence interval based on a Student's T-distribution.
    String
    describe()
    Describe the Summary Statistics.
    double
    getMean()
    The mean.
    double
    getSd()
    The standard deviation.
    double
    getVar()
    The variance.
    String
    toString()
    $

    Methods inherited from class java.lang.Object

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

  • Field Details

    • mean

      public final double mean
      The mean value.

    • var

      public final double var
      The variance.

    • varPopulation

      public final double varPopulation
      The population variance.

    • sd

      public final double sd
      The standard deviation.

    • sdPopulation

      public final double sdPopulation
      The population standard deviation.

    • sumWeights

      public final double sumWeights
      The sum of all weights.

    • min

      public final double min
      The minimum value.

    • max

      public final double max
      The maximum value.

    • count

      public final long count
      The number of entries.

    • sum

      public final double sum
      The sum of all values.

    • dof

      public final long dof
      The number of degrees of freedom.

  • Constructor Details

    • BootStrapStatistics

      public BootStrapStatistics(double[] values)
      Constructs a static summary of a statistic from provided values. Assumes weights are all constant (1.0). Assumes all values will be used.
      Parameters:
      values - Values to summarize.

    • BootStrapStatistics

      public BootStrapStatistics(double[] values, int first)
      Constructs a static summary of a statistic from provided values. Assumes weights are all constant (1.0). Assumes all values from first to end will be used.
      Parameters:
      values - Values to summarize.
      first - First value to use.

    • BootStrapStatistics

      public BootStrapStatistics(double[] values, int first, int last)
      Constructs a static summary of a statistic from provided values. Assumes weights are all constant (1.0). Assumes a stride of 1.
      Parameters:
      values - Values to summarize.
      first - First value to use.
      last - Last value to use.

    • BootStrapStatistics

      public BootStrapStatistics(double[] values, int first, int last, int stride)
      Constructs a static summary of a statistic from provided values. Assumes weights are all constant (1.0).
      Parameters:
      values - Values to summarize.
      first - First value to use.
      last - Last value to use.
      stride - Stride between values used.

    • BootStrapStatistics

      public BootStrapStatistics(double[] values, @Nullable double[] weights, int first, int last, int stride)
      Constructs a static summary of a statistic from provided values.
      Parameters:
      values - Values to summarize.
      weights - Weights for each value.
      first - First value to use.
      last - Last value to use.
      stride - Stride between values used.

  • Method Details

    • confidenceInterval

      public double confidenceInterval()
      Computes a 95% confidence interval based on a Student's T-distribution.
      Returns:
      95% confidence interval.

    • confidenceInterval

      public double confidenceInterval(double alpha)
      Computes a confidence interval based on a Student's T-distribution.
      Parameters:
      alpha - Alpha (e.g. 0.05 for a 95% CI).
      Returns:
      Confidence interval.

    • getMean

      public double getMean()
      The mean.
      Returns:
      Return the mean.

    • getSd

      public double getSd()
      The standard deviation.
      Returns:
      Return the standard deviation.

    • getVar

      public double getVar()
      The variance.
      Returns:
      Return the variance.

    • toString

      public String toString()
      $
      Overrides:
      toString in class Object

    • describe

      public String describe()
      Describe the Summary Statistics.
      Returns:
      Return the description.