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LMest (version 3.0.0)

Generalized Latent Markov Models

Description

Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017).

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Version

Install

install.packages('LMest')

Monthly Downloads

606

Version

3.0.0

License

GPL (>= 2)

Maintainer

Francesco Bartolucci

Last Published

September 12th, 2020

Functions in LMest (3.0.0)

drawLMlatentcont

Draw samples from LM model for continuous outcomes with covariates in the latent model
LMlatentcont-class

Class 'LMlatentcont'
est_mc_basic

Estimate basic Markov chain (MC) model
LMmanifest-class

Class 'LMmanifest'
se

Standard errors
est_mc_cov

Estimate Markov chain (MC) model with covariates
data_SRHS_long

Self-reported health status dataset
MCcov-class

Class 'MCcov'
print

Print the output
data_criminal_sim

Criminal dataset
PSIDlong

Dataset about income dynamics
NLSYlong

National Longitudinal Survey of Youth data
data_drug

Dataset about marijuana consumption
LMest-package

Overview of the Package LMest
LMlatent-class

Class 'LMlatent'
draw_lm_cov_latent_cont

Draw samples from LM model for continuous outcomes with covariaates in the latent model
LMmixed-class

Class 'LMmixed'
MCbasic-class

Class 'MCbasic'
drawLMmixed

Draws samples from the mixed LM model
RLMSdat

Dataset about job satisfaction
decoding

Perform local and global decoding
draw_lm_basic

Draw samples from the basic LM model
LMbasic-class

Class 'LMbasic'
LMbasiccont-class

Class 'LMbasiccont'
draw_lm_mixed

Draws samples from the mixed LM model
est_lm_cov_manifest

Estimate LM model with covariates in the measurement model
bootstrap_lm_cov_latent_cont

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

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

Estimate mixed Latent Markov models
lmestSearch

Search for the global maximum of the log-likelihood
est_lm_basic

Estimate basic LM model
est_lm_basic_cont

Estimate 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
lmestFormula

Formulas for LMest functions
est_lm_mixed

Estimate mixed LM model
summary.lmestData

Summary and plot of lmestData
lmestMc

Estimate Markov Chain models
bootstrap

Parametric bootstrap
RLMSlong

Dataset about job satisfaction
lmestData

Data for LMest functions
drawLMbasic

Draw samples from the basic LM model
drawLMbasiccont

Draw samples from the basic LM model for continuous outcomes
lmestDecoding

Perform local and global decoding
long2matrices

From data in the long format to data in array format
matrices2long

From data in array format to data in long format
long2wide

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

Plots for Generalized Latent Markov Models
est_lm_cov_latent

Estimate LM model with covariates in the latent model
est_lm_cov_latent_cont

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

Estimate Latent Markov models for categorical responses
lmestCont

Estimate Latent Markov models for continuous responses
search.model.LM

Search for the global maximum of the log-likelihood
summary

Summary of LM fits
bootstrap_lm_basic

Parametric bootstrap for the basic LM model
drawLMlatent

Draw samples from LM model with covariates in the latent model
bootstrap_lm_basic_cont

Parametric bootstrap for the basic LM model for continuous outcomes