Package weka.estimators

Class UnivariateMixtureEstimator.MM

java.lang.Object
weka.estimators.UnivariateMixtureEstimator.MM
Enclosing class:
UnivariateMixtureEstimator
public class UnivariateMixtureEstimator.MM extends Object
Fast univariate mixture model implementation.

  • Constructor Summary

    Constructors
    Constructor
    Description
    MM()
     

  • Method Summary

    Modifier and Type
    Method
    Description
    void
    initializeModel(int K, double[] values, double[] weights, Random r)
    Initializes the model.
    double
    logDensity(double value)
    Computes log of density for given value.
    double
    loglikelihood(double[] values, double[] weights)
    Computes loglikelihood of current model.
    double
    MSE()
    Returns average of squared errors for current model.
    double[][]
    predictIntervals(double conf)
    Returns the interval for the given confidence value.
    double
    predictQuantile(double percentage)
    Returns the quantile for the given percentage.
    String
    toString()
    Returns string describing the estimator.

    Methods inherited from class java.lang.Object

    equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

  • Constructor Details

    • MM

      public MM()

  • Method Details

    • toString

      public String toString()
      Returns string describing the estimator.
      Overrides:
      toString in class Object

    • initializeModel

      public void initializeModel(int K, double[] values, double[] weights, Random r)
      Initializes the model. Assumes K >= 1, values.length >= 1, and values.length = weights.length.

    • loglikelihood

      public double loglikelihood(double[] values, double[] weights)
      Computes loglikelihood of current model.

    • MSE

      public double MSE()
      Returns average of squared errors for current model.

    • logDensity

      public double logDensity(double value)
      Computes log of density for given value.

    • predictIntervals

      public double[][] predictIntervals(double conf)
      Returns the interval for the given confidence value.
      Parameters:
      conf - the confidence value in the interval [0, 1]
      Returns:
      the interval

    • predictQuantile

      public double predictQuantile(double percentage)
      Returns the quantile for the given percentage.
      Parameters:
      percentage - the percentage
      Returns:
      the quantile