Package smile.stat.distribution

Class TDistribution

java.lang.Object
smile.stat.distribution.AbstractDistribution
smile.stat.distribution.TDistribution
All Implemented Interfaces:
Serializable, Distribution
public class TDistribution extends AbstractDistribution
Student's t-distribution (or simply the t-distribution) is a probability distribution that arises in the problem of estimating the mean of a normally distributed population when the sample size is small. Student's t-distribution arises when (as in nearly all practical statistical work) the population standard deviation is unknown and has to be estimated from the data. It is the basis of the popular Student's t-tests for the statistical significance of the difference between two sample means, and for confidence intervals for the difference between two population means. The Student's t-distribution is a special case of the generalised hyperbolic distribution.
See Also:

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    final int
    nu
    The degree of freedom.

  • Constructor Summary

    Constructors
    Constructor
    Description
    TDistribution(int nu)
    Constructor.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    cdf(double x)
    Cumulative distribution function.
    double
    cdf2tailed(double x)
    Two-tailed cdf.
    double
    entropy()
    Shannon entropy of the distribution.
    int
    length()
    The number of parameters of the distribution.
    double
    logp(double x)
    The density at x in log scale, which may prevents the underflow problem.
    double
    mean()
    The mean of distribution.
    double
    p(double x)
    The probability density function for continuous distribution or probability mass function for discrete distribution at x.
    double
    quantile(double p)
    The quantile, the probability to the left of quantile is p.
    double
    quantile2tailed(double p)
    Two-tailed quantile.
    double
    rand()
    Generates a random number following this distribution.
    double
    sd()
    The standard deviation of distribution.
    String
    toString()
     
    double
    variance()
    The variance of distribution.

    Methods inherited from class smile.stat.distribution.AbstractDistribution

    inverseTransformSampling, quantile, quantile, rejection

    Methods inherited from class java.lang.Object

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

    Methods inherited from interface smile.stat.distribution.Distribution

    likelihood, logLikelihood, rand

  • Field Details

    • nu

      public final int nu
      The degree of freedom.

  • Constructor Details

    • TDistribution

      public TDistribution(int nu)
      Constructor.
      Parameters:
      nu - degree of freedom.

  • Method Details

    • length

      public int length()
      Description copied from interface: Distribution
      The number of parameters of the distribution. The "length" is in the sense of the minimum description length principle.
      Returns:
      The number of parameters.

    • mean

      public double mean()
      Description copied from interface: Distribution
      The mean of distribution.
      Returns:
      The mean.

    • variance

      public double variance()
      Description copied from interface: Distribution
      The variance of distribution.
      Returns:
      The variance.

    • sd

      public double sd()
      Description copied from interface: Distribution
      The standard deviation of distribution.
      Returns:
      The standard deviation.

    • entropy

      public double entropy()
      Description copied from interface: Distribution
      Shannon entropy of the distribution.
      Returns:
      Shannon entropy.

    • toString

      public String toString()
      Overrides:
      toString in class Object

    • rand

      public double rand()
      Description copied from interface: Distribution
      Generates a random number following this distribution.
      Returns:
      a random number.

    • p

      public double p(double x)
      Description copied from interface: Distribution
      The probability density function for continuous distribution or probability mass function for discrete distribution at x.
      Parameters:
      x - a real number.
      Returns:
      the density.

    • logp

      public double logp(double x)
      Description copied from interface: Distribution
      The density at x in log scale, which may prevents the underflow problem.
      Parameters:
      x - a real number.
      Returns:
      the log density.

    • cdf

      public double cdf(double x)
      Description copied from interface: Distribution
      Cumulative distribution function. That is the probability to the left of x.
      Parameters:
      x - a real number.
      Returns:
      the probability.

    • quantile

      public double quantile(double p)
      Description copied from interface: Distribution
      The quantile, the probability to the left of quantile is p. It is actually the inverse of cdf.
      Parameters:
      p - the probability.
      Returns:
      the quantile.

    • cdf2tailed

      public double cdf2tailed(double x)
      Two-tailed cdf.
      Parameters:
      x - a real number.
      Returns:
      the two-tailed cdf.

    • quantile2tailed

      public double quantile2tailed(double p)
      Two-tailed quantile.
      Parameters:
      p - a probability.
      Returns:
      the two-tailed quantile.