Class DiscreteMixture

java.lang.Object
smile.stat.distribution.DiscreteDistribution
smile.stat.distribution.DiscreteMixture
All Implemented Interfaces:
Serializable, Distribution
Direct Known Subclasses:
DiscreteExponentialFamilyMixture

public class DiscreteMixture extends DiscreteDistribution
The finite mixture of discrete distributions.
See Also:
  • Field Details

  • Constructor Details

    • DiscreteMixture

      public DiscreteMixture(DiscreteMixture.Component... components)
      Constructor.
      Parameters:
      components - a list of discrete distributions.
  • Method Details

    • posteriori

      public double[] posteriori(int x)
      Returns the posteriori probabilities.
      Parameters:
      x - an integer value.
      Returns:
      the posteriori probabilities.
    • map

      public int map(int x)
      Returns the index of component with maximum a posteriori probability.
      Parameters:
      x - an integer value.
      Returns:
      the index of component with maximum a posteriori probability.
    • mean

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

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

      public double entropy()
      Shannon's entropy. Not supported.
      Returns:
      Shannon entropy.
    • p

      public double p(int x)
      Description copied from class: DiscreteDistribution
      The probability mass function.
      Specified by:
      p in class DiscreteDistribution
      Parameters:
      x - a real value.
      Returns:
      the probability.
    • logp

      public double logp(int x)
      Description copied from class: DiscreteDistribution
      The probability mass function in log scale.
      Specified by:
      logp in class DiscreteDistribution
      Parameters:
      x - a real value.
      Returns:
      the log probability.
    • 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.
    • rand

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

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

      public int size()
      Returns the number of components in the mixture.
      Returns:
      the number of components in the mixture.
    • bic

      public double bic(double[] data)
      Returns the BIC score.
      Parameters:
      data - the data to calculate likelihood.
      Returns:
      the BIC score.
    • toString

      public String toString()
      Overrides:
      toString in class Object