Package dev.nm.stat.regression.linear.glm

Class GLMResiduals

java.lang.Object

dev.nm.stat.regression.linear.residualanalysis.LMResiduals

dev.nm.stat.regression.linear.glm.GLMResiduals

Direct Known Subclasses:

QuasiGLMResiduals

public class GLMResiduals
extends LMResiduals

Residual analysis of the results of a Generalized Linear Model regression.

Over-dispersion occurs when the observed variance of the data is larger than the predicted variance.

Deviance measures the goodness-of-fit of a model

Constructor Summary

Constructors

Constructor	Description
GLMResiduals(GLMProblem problem, Vector fitted)	Performs residual analysis for a GLM regression.

Method Summary

Modifier and Type	Method	Description
double	deviance()	Gets the (total) deviance.
ImmutableVector	devianceResiduals()	Gets the deviances residuals.
double[]	deviances()	Gets the deviances of the observations.
double	overdispersion()	Gets the over-dispersion.

Methods inherited from class dev.nm.stat.regression.linear.residualanalysis.LMResiduals

AR2, df, fitted, Fstat, getProblem, hHat, leverage, R2, residuals, RSS, standardized, stderr, studentized, TSS, weightedFittedValues, weightedResiduals

Methods inherited from class java.lang.Object

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

Constructor Detail

GLMResiduals

public GLMResiduals(GLMProblem problem,
                    Vector fitted)

Performs residual analysis for a GLM regression.

Parameters:

problem - the GLM problem to be solved

fitted - the fitted values

Method Detail

overdispersion

public double overdispersion()

Gets the over-dispersion.

Returns:

the over-dispersion

deviances

public double[] deviances()

Gets the deviances of the observations.

Returns:

the deviances

deviance

public double deviance()

Gets the (total) deviance.

Returns:

the (total) deviance

devianceResiduals

public ImmutableVector devianceResiduals()

Gets the deviances residuals.

Returns:

the deviances residuals