Uses of Class
dev.nm.stat.regression.linear.glm.GLMProblem
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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 -
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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 aGeneralizedLinearModel
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)
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