>
Fa   |   Ar   |   En
   Lmest: An R package for latent Markov models for longitudinal categorical data  
   
نویسنده bartolucci f. ,pandolfi s. ,pennoni f.
منبع journal of statistical software - 2017 - دوره : 81 - شماره : 0
چکیده    Latent markov (lm) models represent an important class of models for the analysis of longitudinal data,especially when response variables are categorical. these models have a great potential of application in many fields,such as economics and medicine. we illustrate the r package lmest that is tailored to deal with the basic lm model and some extended formulations accounting for individual covariates and for the presence of unobserved clusters of units having the same initial and transition probabilities (mixed lm model). the main functions of the package are tailored to parameter estimation through the expectation-maximization algorithm,which is based on suitable forwardbackward recursions. the package also permits local and global decoding and to obtain standard errors for the parameter estimates. we illustrate the use of the package and its main features through some empirical examples in the fields of labour market,health,and criminology. © 2017,american statistical association. all rights reserved.
کلیدواژه Expectation-maximization algorithm; Forward-backward recursions; Hidden Markov model; Missing data
آدرس department of economics,university of perugia,via a. pascoli,perugia,06123, Italy, department of economics,university of perugia,via a. pascoli,perugia,06123, Italy, university of milano-bicocca,italy,department of statistics,quantitative methods,via bicocca degli arcimboldi 8,milano,20126, Italy
 
     
   
Authors
  
 
 

Copyright 2023
Islamic World Science Citation Center
All Rights Reserved