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Sally Paganin
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NIMBLE: MCMC, particle filtering, and programmable hierarchical modeling
P de Valpine, C Paciorek, D Turek, N Michaud, C Anderson-Bergman, ...
R package version 0.11 1, 2021
105*2021
NIMBLE user manual
P de Valpine, C Paciorek, D Turek, N Michaud, C Anderson-Bergman, ...
R package manual version 0.9 1, 2020
37*2020
Centered partition processes: Informative priors for clustering (with discussion)
S Paganin, AH Herring, AF Olshan, DB Dunson, TNBDP Study
Bayesian analysis 16 (1), 301, 2021
182021
NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling. 2020
P de Valpine, C Adler, D Turek, N Michaud, C Anderson-Bergman, ...
R package version 0.12 2, 2020
142020
Bayesian modeling of networks in complex business intelligence problems
D Durante, S Paganin, B Scarpa, DB Dunson
Journal of the Royal Statistical Society: Series C (Applied Statistics) 66 …, 2015
122015
Nimble: MCMC, Particle Filtering, and Programmable Hierarchical Modeling. R package version 0.9. 1
P de Valpine, C Paciorek, D Turek, N Michaud, C Anderson-Bergman, ...
92020
Computational strategies and estimation performance with Bayesian semiparametric Item Response Theory models
S Paganin, CJ Paciorek, C Wehrhahn, A Rodriguez, S Rabe-Hesketh, ...
arXiv preprint arXiv:2101.11583, 2021
8*2021
Bayesian nonparametric latent class analysis for different item types
M Qiu, S Paganin, I Ohn, L Lin
Multivariate Behavioral Research 58 (1), 156-157, 2023
22023
Informed Random Partition Models with Temporal Dependence
S Paganin, GL Page, FA Quintana
arXiv preprint arXiv:2311.14502, 2023
12023
Computational methods for fast Bayesian model assessment via calibrated posterior p-values
S Paganin, P de Valpine
arXiv preprint arXiv:2306.04866, 2023
2023
Allergic Rhinitis and Asthma: Relationship with Transverse Maxillary Contraction and Transverse Expansion Stability in Children
G Ottaviano, L Favero, S Hajrulla, A Volpato, S Paganin, G Bissolotti, ...
Applied Sciences 13 (5), 3200, 2023
2023
New Frontiers in Bayesian Statistics: BAYSM 2021, Online, September 1–3
R Argiento, F Camerlenghi, S Paganin
Springer Nature, 2022
2022
Package ‘compareMCMCs’
P de Valpine, S Paganin, D Turek, C Paciorek
2022
compareMCMCs: An R package for studying MCMC efficiency
P de Valpine, S Paganin, D Turek
Journal of Open Source Software 7 (69), 3844, 2022
2022
Semiparametric IRT models for non-normal latent traits
S Paganin
CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS, 178, 2021
2021
Bayesian IRT models in NIMBLE.
S Paganin, C Paciorek, P de Valpine
Book of Short Papers SIS 2020, 644-649, 2020
2020
Domain knowledge based priors for clustering
S Paganin
Proceedings of the Conference of the Italian Statistical Society" Smart …, 2019
2019
Discussion on:" Latent nested nonparametric priors", Federico Camerlenghi, David B. Dunson, Antonio Lijoi, Igor Prünster, Abel Rodríguez, Bayesian Analysis 14, 4, 1303–1356
E Aliverti, S Paganin, T Rigon, M Russo
BAYESIAN ANALYSIS, 2019
2019
Prior-driven cluster allocation in bayesian mixture models
S Paganin
University of Padova, 2018
2018
Hierarchical Graphical Model for Learning Functional Network Determinants
E Aliverti, L Forastiere, T Padellini, S Paganin, E Wit
Studies in Neural Data Science, 23-36, 2017
2017
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Articles 1–20