'LMmanifest'An S3 class object created by lmest for Latent Markov (LM) model with covariates in the measurement model.
vector of cut-points
support points for the latent states
estimate of the vector of regression parameters
sigma of the AR(1) process (mod = "FM")
parameter vector for AR(1) process (mod = "FM")
vector of initial probabilities
transition matrix
maximum log-likelihood
number of parameters
optimal number of latent states
value of the Akaike Information Criterion
value of Bayesian Information Criterion
number of observations in the data
number of time occasions
for LM model with covariates on the manifest model: "LM" = Latent Markov with stationary transition, "FM" = finite mixture model where a mixture of AR(1) processes is estimated with common variance and specific correlation coefficients
standard errors for the regression parameters be
standard errors for logit type transformation of rho
information matrix
array containing the posterior distribution of the latent states for each units and time occasion
prediction of the overall latent effect
array containing the available response configurations
vector of frequencies of the available configurations
matrix containing the marginal distribution of the latent states
vector containing the values of the log-likelihood of the LM model with each k (latent states)
vector containing the values of the BIC for each k
vector containing the values of the AIC for each k
command used to call the function
data frame given in input
Francesco Bartolucci, Silvia Pandolfi, Fulvia Pennoni, Alessio Farcomeni, Alessio Serafini
lmest