LMbasiccont-class {LMest} | R Documentation |
Class 'LMbasiccont'
Description
An S3 class object created by lmestCont
function for the latent Markov (LM) model for continuous responses in long format.
Value
lk |
maximum log-likelihood |
piv |
estimate of initial probability vector |
Pi |
estimate of transition probability matrices (k x k x TT) |
Mu |
estimate of conditional means of the response variables (r x k) |
Si |
estimate of var-cov matrix common to all states (r 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 |
n |
number of observations in the data |
TT |
number of time occasions |
modBasic |
model on the transition probabilities: default 0 for time-heterogeneous transition matrices, 1 for time-homogeneous transition matrices, 2 for partial time homogeneity based on two transition matrices one from 2 to (TT-1) and the other for TT |
sepiv |
standard errors for the initial probabilities |
sePi |
standard errors for the transition probabilities |
seMu |
standard errors for the conditional means |
seSi |
standard errors for the var-cov matrix |
sc |
score vector |
J |
information matrix |
Lk |
vector containing the values of the log-likelihood of the LM model with each |
Bic |
vector containing the values of the BIC of the LM model with each |
Aic |
vector containing the values of the AIC of the LM model with each |
V |
array containing the posterior distribution of the latent states for each units and time occasion |
Ul |
matrix containing the predicted sequence of latent states by the local decoding method |
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