Uses of Class
dev.nm.stat.regression.linear.glm.GLMProblem

Packages that use GLMProblem

Package	Description
dev.nm.stat.regression.linear.glm
dev.nm.stat.regression.linear.glm.modelselection
dev.nm.stat.regression.linear.glm.quasi

Uses of GLMProblem in dev.nm.stat.regression.linear.glm

Methods in dev.nm.stat.regression.linear.glm with parameters of type GLMProblem

Modifier and Type	Method	Description
void	GLMFitting.fit(GLMProblem problem, Vector beta0Initial)	Fits a Generalized Linear Model.
void	IWLS.fit(GLMProblem probelm, Vector beta0Initial)

Constructors in dev.nm.stat.regression.linear.glm with parameters of type GLMProblem

Modifier	Constructor	Description
	GeneralizedLinearModel(GLMProblem problem)	Solves a generalized linear problem using the Iterative Re-weighted Least Squares algorithm.
	GeneralizedLinearModel(GLMProblem problem, GLMFitting fitting)	Constructs a GeneralizedLinearModel instance.
	GLMResiduals(GLMProblem problem, Vector fitted)	Performs residual analysis for a GLM regression.

Uses of GLMProblem in dev.nm.stat.regression.linear.glm.modelselection

Methods in dev.nm.stat.regression.linear.glm.modelselection that return GLMProblem

Modifier and Type	Method	Description
GLMProblem	GLMModelSelection.problem()	Returns the original GLM problem.

Methods in dev.nm.stat.regression.linear.glm.modelselection with parameters of type GLMProblem

Modifier and Type	Method	Description
int	BackwardElimination.Step.eliminate(GLMProblem problem, Matrix subA)
int	EliminationByAIC.eliminate(GLMProblem problem, Matrix subA)
int	EliminationByZValue.eliminate(GLMProblem problem, Matrix subA)
int	ForwardSelection.Step.select(GLMProblem problem, Matrix subA, int[] factorChoices)
int	SelectionByAIC.select(GLMProblem problem, Matrix subA, int[] factorChoices)
int	SelectionByZValue.select(GLMProblem problem, Matrix subA, int[] factorChoices)

Constructors in dev.nm.stat.regression.linear.glm.modelselection with parameters of type GLMProblem

Modifier	Constructor	Description
	BackwardElimination(GLMProblem problem)	Constructs a GLM model using the backward elimination method, with EliminationByAIC as the default algorithm.
	BackwardElimination(GLMProblem problem, BackwardElimination.Step step)	Constructs a GLM model using the backward elimination method.
	ForwardSelection(GLMProblem problem)	Constructs a GLM model using the forward selection method, with SelectionByAIC as the default algorithm.
	ForwardSelection(GLMProblem problem, ForwardSelection.Step step)	Constructs a GLM model using the forward selection method.
protected	GLMModelSelection(GLMProblem problem)	Constructs automatically a GLM model to explain the observations.

Uses of GLMProblem in dev.nm.stat.regression.linear.glm.quasi

Subclasses of GLMProblem in dev.nm.stat.regression.linear.glm.quasi

Modifier and Type	Class	Description
class	QuasiGLMProblem	This class represents a quasi generalized linear regression problem.

Methods in dev.nm.stat.regression.linear.glm.quasi with parameters of type GLMProblem

Modifier and Type	Method	Description
void	QuasiGLMNewtonRaphson.fit(GLMProblem problem, Vector beta0Initial)