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LMest (version 3.2.0)

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

580

Version

3.2.0

License

GPL (>= 2)

Maintainer

Francesco Bartolucci

Last Published

August 30th, 2024

Functions in LMest (3.2.0)

bootstrap

Parametric bootstrap
LMbasic-class

Class 'LMbasic'
LMbasiccont-class

Class 'LMbasiccont'
bootstrap_lm_basic

Parametric bootstrap for the basic LM model
MCcov-class

Class 'MCcov'
MCbasic-class

Class 'MCbasic'
data_SRHS_long

Self-reported health status dataset
bootstrap_lm_basic_cont

Parametric bootstrap for the basic LM model for continuous outcomes
bootstrap_lm_cov_latent

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

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

Employment dataset
draw_lm_basic

Draw samples from the basic LM model
draw_lm_basic_cont

Draw samples from the basic LM model for continuous outcomes
PSIDlong

Dataset about income dynamics
decoding

Perform local and global decoding
data_heart_sim

Health dataset
NLSYlong

National Longitudinal Survey of Youth data
draw

Draw simulated sample from a Generalized Latent Markov Model
RLMSdat

Dataset about job satisfaction
draw_lm_mixed

Draws samples from the mixed LM model
est_lm_mixed

Estimate mixed LM model
est_lm_basic

Estimate basic LM model
lmestDecoding

Perform local and global decoding
lmestSearch

Search for the global maximum of the log-likelihood
long2matrices

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

Estimate LM model with covariates in the latent model
est_lm_basic_cont

Estimate basic LM model for continuous outcomes
est_mc_basic

Estimate basic Markov chain (MC) model
lmestCont

Estimate Latent Markov models for continuous responses
lmestData

Data for LMest functions
long2wide

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

From data in array format to data in long format
print

Print the output
plot

Plots for Generalized Latent Markov Models
lmestFormula

Formulas for LMest functions
data_drug

Dataset about marijuana consumption
est_lm_cov_latent_cont

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

Criminal dataset
RLMSlong

Dataset about job satisfaction
data_market_sim

Marketing dataset
data_long_cont

Multivariate Longitudinal Continuous (Gaussian) Data
est_lm_cov_manifest

Estimate LM model with covariates in the measurement model
se

Standard errors
est_mc_cov

Estimate Markov chain (MC) model with covariates
lmest

Estimate Latent Markov models for categorical responses
draw_lm_cov_latent

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

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

Summary of LM fits
lmestMc

Estimate Markov Chain models
lmestMixed

Estimate mixed Latent Markov models
search.model.LM

Search for the global maximum of the log-likelihood
summary.lmestData

Summary and plot of lmestData
LMest-package

Overview of the Package LMest
LMlatent-class

Class 'LMlatent'
LMmixed-class

Class 'LMmixed'
LMmanifestcont-class

Class 'LMmanifestcont'
LMlatentcont-class

Class 'LMlatentcont'
LMmanifest-class

Class 'LMmanifest'