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Francesco Bartolucci
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2020 – today
- 2024
- [j30]Fulvia Pennoni
, Francesco Bartolucci, Silvia Pandolfi:
Variable Selection for Hidden Markov Models with Continuous Variables and Missing Data. J. Classif. 41(3): 568-589 (2024) - [j29]Fulvia Pennoni
Erratum to: Variable Selection for Hidden Markov Models with Continuous Variables and Missing Data. J. Classif. 41(3): 590 (2024) - [j28]Luca Brusa, Fulvia Pennoni, Francesco Bartolucci:
Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms. Stat. Comput. 34(1): 62 (2024) - 2023
- [j27]Luca Brusa
Tempered expectation-maximization algorithm for the estimation of discrete latent variable models. Comput. Stat. 38(3): 1391-1424 (2023) - [j26]Luca Brusa
Correction to: Tempered expectation-maximization algorithm for the estimation of discrete latent variable models. Comput. Stat. 38(3): 1425 (2023) - 2022
- [j25]Ewa Genge
Are attitudes toward immigration changing in Europe? An analysis based on latent class IRT models. Adv. Data Anal. Classif. 16(2): 235-271 (2022) - 2021
- [j24]David Aristei
A bivariate finite mixture growth model with selection. Adv. Data Anal. Classif. 15(3): 759-793 (2021) - 2020
- [j23]Francesco Bartolucci, Silvia Pandolfi:
An exact algorithm for time-dependent variational inference for the dynamic stochastic block model. Pattern Recognit. Lett. 138: 362-369 (2020)
2010 – 2019
- 2019
- [j22]Francesco Bartolucci
Comment on: The class of CUB models: statistical foundations, inferential issues and empirical evidence. Stat. Methods Appl. 28(3): 437-439 (2019) - 2018
- [j21]Francesco Bartolucci
Latent Ignorability and Item Selection for Nursing Home Case-Mix Evaluation. J. Classif. 35(1): 172-193 (2018) - [j20]Francesco Bartolucci
Dealing with reciprocity in dynamic stochastic block models. Comput. Stat. Data Anal. 123: 86-100 (2018) - 2016
- [j19]Michela Gnaldi, Silvia Bacci
A multilevel finite mixture item response model to cluster examinees and schools. Adv. Data Anal. Classif. 10(1): 53-70 (2016) - [j18]Francesco Bartolucci
Item selection by latent class-based methods: an application to nursing home evaluation. Adv. Data Anal. Classif. 10(2): 245-262 (2016) - [j17]Silvia Bacci
Two-Tier Latent Class IRT Models in R. R J. 8(2): 139 (2016) - 2015
- [j16]Francesco Bartolucci
Three-step estimation of latent Markov models with covariates. Comput. Stat. Data Anal. 83: 287-301 (2015) - [j15]Simone Borsci
Assessing User Satisfaction in the Era of User Experience: Comparison of the SUS, UMUX, and UMUX-LITE as a Function of Product Experience. Int. J. Hum. Comput. Interact. 31(8): 484-495 (2015) - [j14]Francesco Bartolucci
A comparison between the g-index and the h-index based on concentration. J. Assoc. Inf. Sci. Technol. 66(12): 2708-2710 (2015) - [j13]Francesco Bartolucci
Information matrix for hidden Markov models with covariates. Stat. Comput. 25(3): 515-526 (2015) - 2014
- [j12]Silvia Bacci
Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data. Comput. Stat. Data Anal. 71: 262-272 (2014) - [j11]Francesco Bartolucci
MultiLCIRT: An R package for multidimensional latent class item response models. Comput. Stat. Data Anal. 71: 971-985 (2014) - [j10]Silvia Pandolfi, Francesco Bartolucci
A generalized multiple-try version of the Reversible Jump algorithm. Comput. Stat. Data Anal. 72: 298-314 (2014) - [j9]Francesco Bartolucci
A New Constant Memory Recursion for Hidden Markov Models. J. Comput. Biol. 21(2): 99-117 (2014) - [j8]Francesco Bartolucci
Comment on the paper "On the memory complexity of the forward-backward algorithm, " by Khreich W., Granger E., Miri A., Sabourin, R. Pattern Recognit. Lett. 38: 15-19 (2014) - 2012
- [j7]Francesco Bartolucci
Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data. Comput. Stat. Data Anal. 56(12): 4067-4080 (2012) - [j6]Francesco Bartolucci
On a possible decomposition of the h-index. J. Assoc. Inf. Sci. Technol. 63(10): 2126-2127 (2012) - 2010
- [c1]Silvia Pandolfi, Francesco Bartolucci, Nial Friel:
A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection. AISTATS 2010: 581-588
2000 – 2009
- 2007
- [j5]Francesco Bartolucci
Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data. Comput. Stat. Data Anal. 51(7): 3470-3483 (2007) - 2005
- [j4]Francesco Bartolucci
Clustering Univariate Observations via Mixtures of Unimodal Normal Mixtures. J. Classif. 22(2): 203-219 (2005) - [j3]Francesco Bartolucci
The use of mixtures for dealing with non-normal regression errors. Comput. Stat. Data Anal. 48(4): 821-834 (2005) - 2004
- [j2]Francesco Bartolucci
Testing for positive association in contingency tables with fixed margins. Comput. Stat. Data Anal. 47(1): 195-210 (2004) - 2003
- [j1]Francesco Bartolucci
Likelihood-based inference for asymmetric stochastic volatility models. Comput. Stat. Data Anal. 42(3): 445-449 (2003)
Coauthor Index
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