diagnose: Diagnostics for the model fit.

In inarmix: Mixture models for longitudinal count data.

Description

Provides diagnostics of the mixture model fit.

Usage

diagnose(results)

Arguments

results

An object of class "inarmix"

Value

An object of class "diagnose.inarmix" which is a list containing the following components

em.converged	An indication of whether or not the "EM algorithm" converged.
niter	The number of iterations for required for the EM algorithm to converge.
nclasses	The number of latent classes used in the model fit.
loglikhood	The values of the log-likelihood function at each EM iteration.
ConvMat	This is a matrix containing several pieces of information. The columns with GEE in the title indicate if the algorithms for updating the parameters within an EM iteration have converged. The column with l[i] just contains the log-likelihood value. The column with the title "||Psi^2||" gives the norm of the "global estimating equation" - this should be near zero if the algorithm converged.

Author(s)

Nicholas Henderson

Examples

XX <- cbind(rep(1,9),c(0:8)/4)
colnames(XX) <- c("const","time")
coefs <- rbind(c(-.2,0),c(1.2,.3))
alpha <- c(.2,.2)
scale <- c(2,2)
mix.prop <- c(.8,.2)

testdat <- GenerateMixData(200,coefs,alpha,scale,mix.prop,XX)
testfit <- inarmix(y~time,nclasses=2,id=subject,data=testdat,maxiter=3)

diagnose(testfit)

inarmix documentation built on May 2, 2019, 5:11 a.m.