LMlatent-class: Class "LMlatent"

In LMest: Generalized Latent Markov Models

Class 'LMlatent'

Description

An S3 class object created by lmest for Latent Markov (LM) model with covariates in the latent model.

Value

lk	maximum log-likelihood
Be	estimated array of the parameters affecting the logit for the initial probabilities
Ga	estimated array of the parameters affecting the logit for the transition probabilities
Piv	estimate of initial probability matrix. The first state is used as reference category when param = "multilogit"
PI	estimate of transition probability matrices. State u is used as reference category when paramLatent = "multilogit"
Psi	estimate of conditional response probabilities (mb x k x r)
np	number of free parameters
k	optimal number of latent states
aic	value of the Akaike Information Criterion for model selection
bic	value of the Bayesian Information Criterion for model selection
lkv	log-likelihood trace at every step of the EM algorithm
n	number of observations in the data
TT	number of time occasions
paramLatent	type of parametrization for the transition probabilities ("multilogit" = standard multinomial logit for every row of the transition matrix, "difflogit" = multinomial logit based on the difference between two sets of parameters)
sePsi	standard errors for the conditional response matrix
seBe	standard errors for Be
seGa	standard errors for Ga
Lk	vector containing the values of the log-likelihood of the LM model with each k (latent states)
Bic	vector containing the values of the BIC for each k
Aic	vector containing the values of the AIC for each k
V	array containing the posterior distribution of the latent states for each response configuration and time occasion
Ul	matrix containing the predicted sequence of latent states by the local decoding method
S	array containing the available response configurations
yv	vector of frequencies of the available configurations
Pmarg	matrix containing the marginal distribution of the latent states
call	command used to call the function
data	Data frame given in input

Author(s)

Francesco Bartolucci, Silvia Pandolfi, Fulvia Pennoni, Alessio Farcomeni, Alessio Serafini

See Also

lmest

LMest documentation built on Aug. 27, 2023, 5:06 p.m.