Bias-adjusted three-step latent Markov modeling with covariates R Di Mari, DL Oberski, JK Vermunt Structural Equation Modeling: A Multidisciplinary Journal 23 (5), 649-660, 2016 | 30 | 2016 |

Mostly harmless direct effects: A comparison of different latent Markov modeling approaches R Di Mari, Z Bakk Structural Equation Modeling: A Multidisciplinary Journal 25 (3), 467-483, 2018 | 18 | 2018 |

A data driven equivariant approach to constrained Gaussian mixture modeling R Rocci, SA Gattone, R Di Mari Advances in Data Analysis and Classification 12 (2), 235-260, 2018 | 14 | 2018 |

Clusterwise linear regression modeling with soft scale constraints R Di Mari, R Rocci, SA Gattone International Journal of Approximate Reasoning 91, 160-178, 2017 | 13 | 2017 |

Dynamic discrete mixtures for high-frequency prices L Catania, R Di Mari, P Santucci de Magistris Journal of Business & Economic Statistics 40 (2), 559-577, 2022 | 6 | 2022 |

A random-covariate approach for distal outcome prediction with latent class analysis R Di Mari, Z Bakk, A Punzo Structural Equation Modeling: A Multidisciplinary Journal 27 (3), 351-368, 2020 | 6 | 2020 |

Hierarchical Markov-switching models for multivariate integer-valued time-series L Catania, R Di Mari Journal of Econometrics 221 (1), 118-137, 2021 | 5 | 2021 |

Two-stage multilevel latent class analysis with covariates in the presence of direct effects Z Bakk, R Di Mari, J Oser, J Kuha Structural Equation Modeling: A Multidisciplinary Journal 29 (2), 267-277, 2022 | 2 | 2022 |

Scale-constrained approaches for maximum likelihood estimation and model selection of clusterwise linear regression models R Di Mari, R Rocci, SA Gattone Statistical Methods & Applications 29 (1), 49-78, 2020 | 2 | 2020 |

Hierarchical hidden Markov models for multivariate integer-valued time-series L Catania, R Di Mari Journal of Econometrics, 2020 | 1 | 2020 |

A generalized coefficient of determination for mixtures of regressions R Di Mari, S Ingrassia, A Punzo Conference of the International Federation of Classification Societies, 27-35, 2019 | 1 | 2019 |

Assessing measurement invariance for longitudinal data through latent Markov models R Di Mari, F Dotto, A Farcomeni, A Punzo Structural Equation Modeling: A Multidisciplinary Journal 29 (3), 381-393, 2022 | | 2022 |

A two-step estimator for generalized linear models for longitudinal data with time-varying measurement error R Di Mari, A Maruotti Advances in Data Analysis and Classification, 1-28, 2021 | | 2021 |

LASSO-penalized clusterwise linear regression modeling with Local Least Angle Regression (L-LARS) R Di Mari, R Rocci, SA Gattone Available at SSRN 3832769, 2021 | | 2021 |

Dynamic Discrete Mixtures for High-Frequency Prices C Leopoldo, R Di Mari, P Santucci de Magistris | | 2021 |

Stepwise Estimation of Multilevel Latent Class Models Z Bakk, R di Mari, J Oser, J Kuha Preface XIX 1 Plenary Sessions, 171, 2021 | | 2021 |

Supplementary document to Dynamic Discrete Mixtures for High Frequency Prices L Catania, R Di Mari, PS de Magistris | | 2020 |

Penalized Versus Constrained Approaches for Clusterwise Linear Regression Modeling R Di Mari, SA Gattone, R Rocci Scientific Meeting of the Classification and Data Analysis Group of the …, 2019 | | 2019 |

Constrained maximum likelihood estimation of clusterwise linear regression models with unknown number of components R Di Mari, R Rocci, SA Gattone arXiv preprint arXiv:1804.05185, 2018 | | 2018 |

Cluster-weighted latent class modeling R Di Mari, A Punzo, Z Bakk arXiv preprint arXiv:1801.01464, 2018 | | 2018 |