20 citations · 39 across the 5 of their papers we have counts for
5 papers
Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets
Vincenzo Lagani, Giorgos Athineou, Alessio Farcomeni +2
The statistically equivalent signature (SES) algorithm is a method for feature selection inspired by the principles of constrained-based learning of Bayesian Networks. Most of the…
LMest: an R package for latent Markov models for categorical longitudinal data
Francesco Bartolucci, Alessio Farcomeni, Silvia Pandolfi +1
Latent Markov (LM) models represent an important class of models for the analysis of longitudinal data (Bartolucci et. al., 2013), especially when response variables are categorica…
Longitudinal quantile regression in presence of informative drop-out through longitudinal-survival joint modeling
Alessio Farcomeni, Sara Viviani
We propose a joint model for a time-to-event outcome and a quantile of a continuous response repeatedly measured over time. The quantile and survival processes are associated via s…
Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data
Francesco Bartolucci, Luisa Scaccia, Alessio Farcomeni
We develop a Bayesian approach for selecting the model which is the most supported by the data within a class of marginal models for categorical variables formulated through equali…
An overview of latent Markov models for longitudinal categorical data
F. Bartolucci, A. Farcomeni, F. Pennoni
We provide a comprehensive overview of latent Markov (LM) models for the analysis of longitudinal categorical data. The main assumption behind these models is that the response var…