weka.estimators

Class UnivariateMixtureEstimator.MM

java.lang.Object

weka.estimators.UnivariateMixtureEstimator.MM

Enclosing class:

UnivariateMixtureEstimator

public class UnivariateMixtureEstimator.MM
extends java.lang.Object

Fast univariate mixture model implementation.

Constructor Summary

Constructors

Constructor and Description
MM()

Method Summary

Modifier and Type	Method and Description
void	initializeModel(int K, double[] values, double[] weights, java.util.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.
java.lang.String	toString() Returns string describing the estimator.

Methods inherited from class java.lang.Object

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

Constructor Detail

MM

public MM()

Method Detail

toString

public java.lang.String toString()

Returns string describing the estimator.

Overrides:

toString in class java.lang.Object

initializeModel

public void initializeModel(int K,
                            double[] values,
                            double[] weights,
                            java.util.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