Likelihood-based inference for asymmetric stochastic volatility models. - Francesco Bartolucci; Giovanni De Luca (Comput. Stat. Data Anal., 2003)

Testing for positive association in contingency tables with fixed margins. - Francesco Bartolucci; Luisa Scaccia (Comput. Stat. Data Anal., 2004)

Clustering Univariate Observations via Mixtures of Unimodal Normal Mixtures. - Francesco Bartolucci (J. Classif., 2005)

The use of mixtures for dealing with non-normal regression errors. - Francesco Bartolucci; Luisa Scaccia (Comput. Stat. Data Anal., 2005)

Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data. - Francesco Bartolucci; Valentina Nigro (Comput. Stat. Data Anal., 2007)

A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection. - Silvia Pandolfi; Francesco Bartolucci; Nial Friel (AISTATS, 2010)

Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data. - Francesco Bartolucci; Luisa Scaccia; Alessio Farcomeni (Comput. Stat. Data Anal., 2012)

On a possible decomposition of the h-index. - Francesco Bartolucci (J. Assoc. Inf. Sci. Technol., 2012)

Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data. - Silvia Bacci; Francesco Bartolucci (Comput. Stat. Data Anal., 2014)

MultiLCIRT: An R package for multidimensional latent class item response models. - Francesco Bartolucci; Silvia Bacci; Michela Gnaldi (Comput. Stat. Data Anal., 2014)

A generalized multiple-try version of the Reversible Jump algorithm. - Silvia Pandolfi; Francesco Bartolucci; Nial Friel (Comput. Stat. Data Anal., 2014)

A New Constant Memory Recursion for Hidden Markov Models. - Francesco Bartolucci; Silvia Pandolfi (J. Comput. Biol., 2014)

Comment on the paper "On the memory complexity of the forward-backward algorithm, " by Khreich W., Granger E., Miri A., Sabourin, R. - Francesco Bartolucci; Silvia Pandolfi (Pattern Recognit. Lett., 2014)

Three-step estimation of latent Markov models with covariates. - Francesco Bartolucci; Giorgio Eduardo Montanari; Silvia Pandolfi (Comput. Stat. Data Anal., 2015)

Assessing User Satisfaction in the Era of User Experience: Comparison of the SUS, UMUX, and UMUX-LITE as a Function of Product Experience. - Simone Borsci; Stefano Federici; Silvia Bacci; Michela Gnaldi; Francesco Bartolucci (Int. J. Hum. Comput. Interact., 2015)

A comparison between the g-index and the h-index based on concentration. - Francesco Bartolucci (J. Assoc. Inf. Sci. Technol., 2015)

Information matrix for hidden Markov models with covariates. - Francesco Bartolucci; Alessio Farcomeni (Stat. Comput., 2015)

Item selection by latent class-based methods: an application to nursing home evaluation. - Francesco Bartolucci; Giorgio Eduardo Montanari; Silvia Pandolfi (Adv. Data Anal. Classif., 2016)

A multilevel finite mixture item response model to cluster examinees and schools. - Michela Gnaldi; Silvia Bacci; Francesco Bartolucci (Adv. Data Anal. Classif., 2016)

Two-Tier Latent Class IRT Models in R. - Silvia Bacci; Francesco Bartolucci (R J., 2016)

Latent Ignorability and Item Selection for Nursing Home Case-Mix Evaluation. - Francesco Bartolucci; Giorgio Eduardo Montanari; Silvia Pandolfi (J. Classif., 2018)

Dealing with reciprocity in dynamic stochastic block models. - Francesco Bartolucci; Maria Francesca Marino; Silvia Pandolfi (Comput. Stat. Data Anal., 2018)

Comment on: The class of CUB models: statistical foundations, inferential issues and empirical evidence. - Francesco Bartolucci; Fulvia Pennoni (Stat. Methods Appl., 2019)

An exact algorithm for time-dependent variational inference for the dynamic stochastic block model. - Francesco Bartolucci; Silvia Pandolfi (Pattern Recognit. Lett., 2020)

A bivariate finite mixture growth model with selection. - David Aristei; Silvia Bacci; Francesco Bartolucci; Silvia Pandolfi (Adv. Data Anal. Classif., 2021)

Are attitudes toward immigration changing in Europe? An analysis based on latent class IRT models. - Ewa Genge; Francesco Bartolucci (Adv. Data Anal. Classif., 2022)

Tempered expectation-maximization algorithm for the estimation of discrete latent variable models. - Luca Brusa; Francesco Bartolucci; Fulvia Pennoni (Comput. Stat., 2023)

Correction to: Tempered expectation-maximization algorithm for the estimation of discrete latent variable models. - Luca Brusa; Francesco Bartolucci; Fulvia Pennoni (Comput. Stat., 2023)

Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms. - Luca Brusa; Fulvia Pennoni; Francesco Bartolucci (Stat. Comput., 2024)

Variable Selection for Hidden Markov Models with Continuous Variables and Missing Data. - Fulvia Pennoni; Francesco Bartolucci; Silvia Pandolfi (J. Classif., 2024)

Erratum to: Variable Selection for Hidden Markov Models with Continuous Variables and Missing Data. - Fulvia Pennoni; Francesco Bartolucci; Silvia Pandolfi (J. Classif., 2024)

On a class of finite mixture models that includes hidden Markov models. - Francesco Bartolucci; Silvia Pandolfi; Fulvia Pennoni (J. Multivar. Anal., 2025)

LMest: An R Package for Estimating Generalized Latent Markov Models. - Fulvia Pennoni; Silvia Pandolfi; Francesco Bartolucci (R J., 2025)

When non-response makes estimates from a census a small area estimation problem: the case of the survey on graduates' employment status in Italy. - Maria Giovanna Ranalli; Fulvia Pennoni; Francesco Bartolucci; Antonietta Mira (Adv. Data Anal. Classif., 2025)