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LMest (version 3.2.2)

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

3.2.2

License

GPL (>= 2)

Maintainer

Francesco Bartolucci

Last Published

September 15th, 2024

Functions in LMest (3.2.2)

LMlatent-class

Class 'LMlatent'
RLMSdat

Dataset about job satisfaction
NLSYlong

National Longitudinal Survey of Youth data
bootstrap_lm_cov_latent_cont

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

Perform local and global decoding
RLMSlong

Dataset about job satisfaction
data_criminal_sim

Criminal dataset
draw

Draw simulated sample from a Generalized Latent Markov Model
data_SRHS_long

Self-reported health status dataset
data_employment_sim

Employment dataset
PSIDlong

Dataset about income dynamics
data_drug

Dataset about marijuana consumption
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_basic

Draw samples from the basic LM model
bootstrap_lm_cov_latent

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

Parametric bootstrap
bootstrap_lm_basic

Parametric bootstrap for the basic LM model
draw_lm_mixed

Draws samples from the mixed LM model
data_heart_sim

Health dataset
est_lm_basic

Estimate basic LM model
matrices2long

From data in array format to data in long format
long2matrices

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

Search for the global maximum of the log-likelihood
long2wide

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

Multivariate Longitudinal Continuous (Gaussian) Data
lmestMc

Estimate Markov Chain models
lmestMixed

Estimate mixed Latent Markov models
data_market_sim

Marketing dataset
draw_lm_cov_latent

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

Estimate basic Markov chain (MC) model
search.model.LM

Search for the global maximum of the log-likelihood
est_lm_mixed

Estimate mixed LM model
se

Standard errors
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
draw_lm_cov_latent_cont

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

Estimate Markov chain (MC) model with covariates
est_lm_cov_manifest

Estimate LM model with covariates in the measurement model
est_lm_cov_latent

Estimate LM model with covariates in the latent model
est_lm_basic_cont

Estimate basic LM model for continuous outcomes
lmestCont

Estimate Latent Markov models for continuous responses
summary

Summary of LM fits
lmestData

Data for LMest functions
lmestDecoding

Perform local and global decoding
summary.lmestData

Summary and plot of lmestData
print

Print the output
plot

Plots for Generalized Latent Markov Models
lmestFormula

Formulas for LMest functions
LMmanifestcont-class

Class 'LMmanifestcont'
LMbasic-class

Class 'LMbasic'
LMlatentcont-class

Class 'LMlatentcont'
LMmixed-class

Class 'LMmixed'
LMmanifest-class

Class 'LMmanifest'
LMbasiccont-class

Class 'LMbasiccont'
MCbasic-class

Class 'MCbasic'
MCcov-class

Class 'MCcov'
LMest-package

Overview of the Package LMest