Software
(see also https://github.com/francescobartolucci)
R packages
LCCR: Latent Class Capture Recapture Models
MLCIRTwithin: Latent Class Item Response Theory Models Under 'Within-Item Multi-Dimensionality' --> Supplementary Material
cquad: Conditional ML for Quadratic Exponential Models for Binary Panel Data (see A Dynamic Model for Binary Panel Data with Unobserved Heterogeneity Admitting a root-n Consistent Conditional Estimator and Testing for state dependence in binary panel data with individual covariates)
MultiLCIRT: Multidimensional Latent Class Item Response Theory Models (see MultiLCIRT: An R package for multidimensional latent class item response models)
LMest: Latent Markov Models with and without Covariates
extRC: Extended RC Models for Contingency Tables
STATA modules
CQUAD: Stata module to perform conditional maximum likelihood estimation of quadratic exponential models (see A Dynamic Model for Binary Panel Data with Unobserved Heterogeneity Admitting a root-n Consistent Conditional Estimator and Testing for state dependence in binary panel data with individual covariates)
Other software
Software described in the paper "A multivariate statistical model to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification" (https://github.com/francescobartolucci/ARMultinomial)
Software described in the paper “A joint model for longitudinal and survival data based on an AR(1) latent process”
Software described in the paper “ Pairwise likelihood inference for nested hidden Markov chain models for multilevel longitudinal data”
Software described in the paper “A finite mixture latent trajectory model for modeling ultrarunners' behavior in a 24-hour race”
Software described in the paper “Information matrix for hidden Markov models with covariates”
Software described in the paper “A multidimensional finite mixture SEM for non-ignorable missing responses to test items”
Software described in the paper “A Dynamic Model for Binary Panel Data with Unobserved Heterogeneity Admitting a root-n Consistent Conditional Estimator"
Software described in the paper “Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data”
Software described in the paper “A latent Markov model for detecting patterns of criminal activity”
Software described in the paper “A class of multidimensional IRT models for testing unidimensionality and clustering items”
Software described in the paper “A class of latent marginal models for capture-recapture data with continuous covariates”
Software described in the paper “Clustering univariate observations via mixtures of unimodal normal mixtures”
Software described in the paper “The Analysis of Capture-Recapture Data with a Rasch-type Model allowing for Conditional Dependence and Multidimensionality