Uses of Class dev.nm.stat.regression.linear.glm.GLMProblem (NM DEV API (v1.2.4) by NM)

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
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
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.
`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)`