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Silvia Pandolfi
Silvia Pandolfi
Associate Professor - Department of Economics - University of Perugia
Verified email at unipg.it
Title
Cited by
Cited by
Year
A comparison of some criteria for states selection in the latent Markov model for longitudinal data
S Bacci, S Pandolfi, F Pennoni
Advances in Data Analysis and Classification 8 (2), 125-145, 2014
582014
LMest: An R package for latent Markov models for longitudinal categorical data
F Bartolucci, S Pandolfi, F Pennoni
Journal of Statistical Software 81, 1-38, 2017
472017
A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection
S Pandolfi, F Bartolucci, PN Friel
Journal of Machine Learning Research - Proceedings of Internationalá…, 2010
432010
Three-step estimation of latent Markov models with covariates
F Bartolucci, GE Montanari, S Pandolfi
Computational Statistics & Data Analysis 83, 287-301, 2015
232015
A generalized multiple-try version of the reversible jump algorithm
S Pandolfi, F Bartolucci, N Friel
Computational Statistics & Data Analysis 72, 298-314, 2014
182014
Dimensionality of the Latent Structure and Item Selection Via Latent Class Multidimensional IRT Models
F Bartolucci, GE Montanari, S Pandolfi
Psychometrika 77, 782-802, 2012
182012
Dealing with reciprocity in dynamic stochastic block models
F Bartolucci, MF Marino, S Pandolfi
Computational Statistics & Data Analysis 123, 86-100, 2018
162018
LMest: an R package for latent Markov models for categorical longitudinal data
F Bartolucci, A Farcomeni, S Pandolfi, F Pennoni
arXiv preprint arXiv:1501.04448, 2015
132015
Latent ignorability and item selection for nursing home case-mix evaluation
F Bartolucci, GE Montanari, S Pandolfi
Journal of Classification 35 (1), 172-193, 2018
92018
Item selection by latent class-based methods: an application to nursing home evaluation
F Bartolucci, GE Montanari, S Pandolfi
Advances in Data Analysis and Classification 10 (2), 245-262, 2016
62016
An exact algorithm for time-dependent variational inference for the dynamic stochastic block model
F Bartolucci, S Pandolfi
Pattern Recognition Letters 138, 362-369, 2020
52020
Evaluation of long-term health care services through a latent Markov model with covariates
GE Montanari, S Pandolfi
Statistical Methods & Applications 27 (1), 151-173, 2018
52018
A new constant memory recursion for hidden Markov models
F Bartolucci, S Pandolfi
Journal of Computational Biology 21 (2), 99-117, 2014
52014
A comparison of some estimation methods for latent Markov models with covariates
F Bartolucci, GE Montanari, S Pandolfi
Proceedings of COMPSTAT, 531-538, 2014
52014
Item selection by an extended Latent Class model: An application to nursing homes evaluation
F Bartolucci, G Montanari, S Pandolfi
Available at SSRN 2040719, 2012
52012
University of Perugia (IT)
F Bartolucci, S Pandolfi
Italy, 2012
52012
A joint model for longitudinal and survival data based on an AR (1) latent process
S Bacci, F Bartolucci, S Pandolfi
Statistical Methods in Medical Research 27 (5), 1285-1311, 2018
42018
A bivariate finite mixture growth model with selection
D Aristei, S Bacci, F Bartolucci, S Pandolfi
Advances in Data Analysis and Classification 15 (3), 759-793, 2021
22021
A generalized Multiple-try Metropolis version of the Reversible Jump algorithm
S Pandolfi, F Bartolucci, N Friel
arXiv preprint arXiv:1006.0621, 2010
22010
A new constant memory recursion for hidden Markov models
S Pandolfi, F Bartolucci
2*
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