{"name":"complk_cont","title":"Complete log-likelihood of the basic latent Markov model for continuous outcomes","pagetitle":"Complete log-likelihood of the basic latent Markov model for continuous outcomes — complk_cont","aliases":"complk_cont","author":"Francesco Bartolucci, Silvia Pandolfi, University of Perugia (IT), http://www.stat.unipg.it/bartolucci","keywords":[],"description":"

Function that computes complete log-likelihood of the basic latent Markov model for continuous outcomes (internal use).

","usage":"complk_cont(Y, piv, Pi, Mu, Si, k)","arguments":[{"name":"Y","description":"

array of continuous outcomes (n x TT x r)

"},{"name":"piv","description":"

vector of initial probabilities

"},{"name":"Pi","description":"

transition probability matrix

"},{"name":"Mu","description":"

matrix of conditional means for the response variables (r x k)

"},{"name":"Si","description":"

var-cov matrix common to all states (r x r)

"},{"name":"k","description":"

number of latent classes

"}],"has_args":true,"sections":[],"value":"

log-likelihood

Phi

matrix of the conditional probabilities of the observed response configurations

matrix of the forward probabilities

vector of marginal probabilities

\n","references":"

Baum, L. E., Petrie, T., Soules, G., and Weiss, N. (1970). \nA maximization technique occurring in the statistical analysis of probabilistic functions \nof Markov chains. Annals of Mathematical Statistics, 41, 164-171.

","package":{"package":"LMest","version":"2.4.5"}}

Description

Usage

Arguments

Value

References