LMmanifest-class {LMest}

Class 'LMmanifest'

Description

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

Value

mu

vector of cut-points

al

support points for the latent states

be

estimate of the vector of regression parameters

si

sigma of the AR(1) process (mod = "FM")

rho

parameter vector for AR(1) process (mod = "FM")

la

vector of initial probabilities

PI

transition matrix

lk

maximum log-likelihood

np

number of parameters

k

optimal number of latent states

aic

value of the Akaike Information Criterion

bic

value of Bayesian Information Criterion

n

number of observations in the data

TT

number of time occasions

modManifest

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

sebe

standard errors for the regression parameters be

selrho

standard errors for logit type transformation of rho

J1

information matrix

V

array containing the posterior distribution of the latent states for each units and time occasion

PRED1

prediction of the overall latent effect

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

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

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