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LMest (version 2.4.5)

Latent Markov Models with and without Covariates

Description

Fit certain versions of the Latent Markov model for longitudinal categorical data.

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Version

Install

install.packages('LMest')

Monthly Downloads

548

Version

2.4.5

License

GPL (>= 2)

Maintainer

Francesco Bartolucci

Last Published

April 7th, 2019

Functions in LMest (2.4.5)

complk_cont

Complete log-likelihood of the basic latent Markov model for continuous outcomes
bootstrap_lm_basic_cont

Parametric bootstrap for the basic LM model for continuous outcomes
draw_lm_basic_cont

Draw samples from the basic LM model for continuous outcomes
draw_lm_cov_latent

Draw samples from LM model with covariaates in the latent model
bootstrap_lm_cov_latent

Parametric bootstrap for LM models with individual covariates in the latent model
est_lm_cov_latent

Estimate LM model with covariates in the latent model
est_lm_cov_manifest

Estimate LM model with covariates in the measurement model
est_lm_cov_latent_cont

Estimate LM model for continuous outcomes with covariates in the latent model
logit1

Compute the logit function with respect to a reference category.
draw_lm_cov_latent_cont

Draw samples from LM model for continuous outcomes with covariaates in the latent model
draw_lm_mixed

Draws samples from the mixed LM model
long2matrices

From data in the long format to data in array format
est_lm_mixed

Estimate mixed LM model
lk_obs_mixed

Compute the observable log-likelihood of the mixed LM model
lk_obs_latent

Compute the observable log-likelihood of the LM model with covariates in the latent model
lk_obs_manifest

Compute the observable log-likelihood of the LM model with covariates in the measurement model
est_lm_basic

Estimate basic LM model
prob_post_cov

Compute posterior probabilities.
est_lm_basic_cont

Estimate basic LM model for continuous outcomes
lk_sta

Compute the stationary log-likelihood
prob_post_cov_cont

Compute posterior probabilities.
est_mc_basic

Estimate basic Markov chain (MC) model
print.LMbasic

Print the output of LMbasic object
print.LMsearch

Print the output of LMsearch object
summary.LMlatentcont

Print the output of LMlatentcont object
summary.LMmanifest

Print the output of LMmanifest object
print.MCbasic

Print the output of MCbasic object
rec3

Recursions used by est_lm_cov_manifest
recursions

Recursions used by est_lm_basic
summary.MCbasic

Print the output of MCbasic object
summary.MClatent

Print the output of MClatent object
est_mc_cov

Estimate Markov chain (MC) model with covariates
blkdiag

Build a block diagonal matrix.
print.LMbasiccont

Print the output of LMbasiccont object
print.LMmanifest

Print the output of LMmanifest object
prod_array

Compute the product of array and vector
rec1

Recursions used by est_lm_cov_manifest
bootstrap_lm_basic

Parametric bootstrap for the basic LM model
summary.LMmixed

Print the output of LMmixed object
data_criminal_sim

Criminal dataset
print.LMmixed

Print the output of LMmixed object
summary.LMsearch

Print the output of LMsearch object
data_drug

Dataset about marijuana consumption
search.model.LM

Search for the global maximum of the log-likelihood
LMest-package

Fit latent Markov models
RLMSdat

Dataset about job satisfaction
sq

Create a matrix with the combination of vectors of (1,0)
expit1

Compute the expit function with respect to a reference category.
invglob

Invert vector of global logits.
lk_ar_rho

Compute complete log-likelihood for AR(1) latent process
lk_comp_latent

Complete log-likelihood of the latent Markov model with covariates
long2wide

From data in the long format to data in the wide format
decoding

Perform local and global decoding
marg_param

Compute marginal parametrization
print.MClatent

Print the output of MClatent object
draw_lm_basic

Draw samples from the basic LM model
prob_multilogit

Compute multinomial probabilities
summary.LMbasiccont

Print the output of LMbasiccont object
est_multilogit

Estimate multilogit model
expit

Compute the expit function.
summary.LMlatent

Print the output of LMlatent object
lk_comp_latent_cont

Complete log-likelihood of the latent Markov model for continuous outcomes with covariates
lk_obs

Compute the observable log-likelihood of the basic LM model
print.LMlatent

Print the output of LMlatent object
print.LMlatentcont

Print the output of LMlatentcont object
stationary

Stationary
summary.LMbasic

Print the output of LMbasic object
trans_par

Convert matrix parametrization
bootstrap_lm_cov_latent_cont

Parametric bootstrap for LM models for continuous outcomes with individual covariates in the latent model
data_SRHS_long

Self-reported health status dataset
complk

Complete log-likelihood of the basic latent Markov model