MGLMreg-class {MGLM}

Class "MGLMreg"

Description

Objects can be created by calls of the form new("MGLMreg", ...).

Slots

call

object of class "call".

data

object of class "list" , consists of both the predictor matrix and the response matrix.

coefficients

object of class "list" or "matrix", the estimated parameters.

SE

object of class "list" or "matrix", the standard errors of the parameters.

test

object of class "matrix", the test statistics and p-values.

Hessian

object of class "matrix", the Hessian matrix.

logL

object of class "numeric", the loglikelihood.

BIC

object of class "numeric",

AIC

object of class "numeric", Akaike information criterion.

iter

object of class "numeric", the number of iteration used.

distribution

object of class "character", the distribution fitted.

fitted

object of class "vector", the fitted value.

gradient

object of class "numeric" or "matrix", the gradient at the estimated parameter values.

wald.value

object of class "numeric" or "logical", the Wald statistics.

wald.p

object of class "numeric" or "logical", the p values of Wald test.

Dof

object of class "numeric", the degrees of freedom.

Author(s)

Yiwen Zhang and Hua Zhou

Examples

showClass("MGLMreg")