MGLM (version 0.2.1)

MGLMsparsereg-class: Class "MGLMsparsereg"

Description

A class containing the results from the MGLMsparsereg.

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 "matrix", the estimated parameters.

logL

object of class "numeric", the loglikelihood.

BIC

object of class "numeric",

AIC

object of class "numeric", Akaike information criterion.

Dof

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

iter

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

maxlambda

object of class "numeric", the maximum tuning parameter that ensures the estimated regression coefficients are not all zero.

lambda

object of class "numeric", the tuning parameter used.

distribution

object of class "character", the distribution fitted.

penalty

Object of class "character", the chosen penalty when running penalized regression.

Examples

# NOT RUN {
showClass("MGLMsparsereg")
# }