Sfoglia per Rivista BAYESIAN ANALYSIS
Adaptive Bayesian density estimation in L^p-metrics with Pitman-Yor or normalized inverse-Gaussian process kernel mixtures
2014 Scricciolo, Catia
An enriched conjugate prior for Bayesian nonparametric inference
2011 Wade, SARA KATHRYN; Mongelluzzo, Silvia; Petrone, Sonia
Bayesian inference and testing of group differences in brain networks
2018 Durante, Daniele; Dunson, David B.
Colombian women's life patterns: a multivariate density regression approach
2022 Wade, Sara; Piccarreta, Raffaella; Cremaschi, Andrea; Antoniano-Villalobos, Isadora
Comment on article by Page and Quintana
2016 Gaetan, Carlo; Padoan, Simone; Pruenster, Igor
Contributed discussion to "Giordano, R., Liu, R., Jordan, M.I., Broderick, T. Evaluating Sensitivity to the Stick-Breaking Prior in Bayesian Nonparametrics (with Discussion). Bayesian Analysis. 2023;18(1):287"
2023 Rebaudo, Giovanni; Fasano, Augusto; Franzolini, Beatrice; Müller, Peter
Fast exact Bayesian inference for sparse signals in the normal sequence model
2021 van Erven, Tim; Szabo, Botond
Generalized quantile treatment effect: a flexible bayesian approach using quantile ratio smoothing
2015 Venturini, Sergio; Dominici, Francesca; Parmigiani, Giovanni
Invited discussion to "Giordano, R., Liu, R., Jordan, M.I., Broderick, T. Evaluating Sensitivity to the Stick-Breaking Prior in Bayesian Nonparametrics (with Discussion). Bayesian Analysis. 2023;18(1):287"
2023 Ascolani, Filippo; Catalano, Marta; Pruenster, Igor
Latent nested nonparametric priors (with discussion)
2019 Camerlenghi, Federico; Dunson, David B.; Lijoi, Antonio; Rodriguez, Abel; Pruenster, Igor
Mean Field Variational Bayes for Elaborate Distributions
2011 Matthew P., Wand; John T., Ormerod; Padoan, Simone; Rudolf, Fruhrwirth
Multilevel linear models, Gibbs samplers and multigrid decompositions (with Discussion)
2021 Zanella, Giacomo; Roberts, Gareth
On the stick-breaking representation for homogeneous NRMIs
2016 Favaro, Stefano; Lijoi, Antonio; Nava, Consuelo; Nipoti, Bernardo; Pruenster, Igor; Teh, Yee Whye
Predictive inference with Fleming-Viot-driven dependent Dirichlet processes
2021 Ascolani, Filippo; Lijoi, Antonio; Ruggiero, Matteo
Stochastic approximations to the Pitman-Yor process
2019 Arbel, Julyan; DE BLASI, Pierpaolo; Pruenster, Igor
Uncertainty quantification for the horseshoe (with discussion)
2017 van der Pas, Stephanie; Szabo, Botond; van der Vaart, Aad
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