Mixed hidden Markov quantile regression models for longitudinal data with possibly incomplete sequences MF Marino, N Tzavidis, M Alfò Statistical methods in medical research 27 (7), 2231-2246, 2018 | 54 | 2018 |
Linear quantile regression models for longitudinal experiments: an overview MF Marino, A Farcomeni Metron 73 (2), 229-247, 2015 | 50 | 2015 |
Mycotoxins and flours: Effect of type of crop, organic production, packaging type on the recovery of fungal genus and mycotoxins C Sacco, R Donato, B Zanella, G Pini, L Pettini, MF Marino, AD Rookmin, ... International Journal of Food Microbiology 334, 108808, 2020 | 24 | 2020 |
Semiparametric empirical best prediction for small area estimation of unemployment indicators MF Marino, MG Ranalli, N Salvati, M Alfò The Annals of Applied Statistics 13 (2), 1166-1197, 2019 | 24 | 2019 |
Dealing with reciprocity in dynamic stochastic block models F Bartolucci, MF Marino, S Pandolfi Computational Statistics & Data Analysis 123, 86-100, 2018 | 20 | 2018 |
M-quantile regression for multivariate longitudinal data with an application to the Millennium Cohort Study M Alfò, MF Marino, MG Ranalli, N Salvati, N Tzavidis Journal of the Royal Statistical Society Series C: Applied Statistics 70 (1 …, 2021 | 18* | 2021 |
Refugees in undeclared employment—a case study in Turkey F Bruckschen, T Koebe, M Ludolph, MF Marino, T Schmid Guide to Mobile Data Analytics in Refugee Scenarios: The'Data for Refugees …, 2019 | 13 | 2019 |
Gaussian quadrature approximations in mixed hidden Markov models for longitudinal data: a simulation study MF Marino, M Alfó Computational statistics & data analysis 94, 193-209, 2016 | 11 | 2016 |
Latent drop-out based transitions in linear quantile hidden Markov models for longitudinal responses with attrition MF Marino, M Alfó Advances in Data Analysis and Classification 9 (4), 483-502, 2015 | 11 | 2015 |
Using finite mixtures of M-quantile regression models to handle unobserved heterogeneity in assessing the effect of meteorology and traffic on air quality S Del Sarto, MF Marino, MG Ranalli, N Salvati Stochastic environmental research and risk assessment 33, 1345-1359, 2019 | 10 | 2019 |
A bi-dimensional finite mixture model for longitudinal data subject to dropout A Spagnoli, MF Marino, Alfo' Marco STATISTICS IN MEDICINE 37 (20), 2998-3011, 2018 | 5 | 2018 |
Extending finite mixtures of latent trait analyzers for bipartite networks F Dalila, MF Marino, F Martella Book of short Papers 2022, 540-550, 2022 | 4 | 2022 |
Finite mixtures of hidden Markov models for longitudinal responses subject to drop out MF Marino, M Alfò Multivariate Behavioral Research 55 (5), 647-663, 2020 | 4* | 2020 |
Multiple imputation and selection of ordinal level 2 predictors in multilevel models: An analysis of the relationship between student ratings and teacher practices and attitudes L Grilli, M Francesca Marino, O Paccagnella, C Rampichini Statistical Modelling 22 (3), 221-238, 2022 | 3 | 2022 |
Correlates of Inter-Districts Migrations in Tanzania. A Gravity-Type Modeling Approach E Pirani, MF Marino, A Petrucci Statistica 79 (2), 201-221, 2019 | 3 | 2019 |
lqmix: an R package for longitudinal data analysis via linear quantile mixtures M Alfó, MF Marino, MG Ranalli, N Salvati arXiv preprint arXiv:2302.11363, 2023 | 2 | 2023 |
Hybrid maximum likelihood inference for stochastic block models MF Marino, S Pandolfi Computational Statistics & Data Analysis 171, 107449, 2022 | 2 | 2022 |
Model-based two-way clustering of second-level units in ordinal multilevel latent Markov models GE Montanari, M Doretti, MF Marino Advances in Data Analysis and Classification 16 (2), 457-485, 2022 | 2 | 2022 |
Biclustering multivariate discrete longitudinal data M Alfó, MF Marino, F Martella Statistics and Computing 34 (1), 42, 2024 | 1 | 2024 |
Finite mixtures of latent trait analyzers with concomitant variables for bipartite networks: an analysis of COVID-19 data D Failli, MF Marino, F Martella MULTIVARIATE BEHAVIORAL RESEARCH, 1-36, 2024 | 1 | 2024 |