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Similarity analysis in Bayesian random partition models
(ELSEVIER, 2011)
This work proposes a method to assess the influence of individual observations in the clustering generated by any process that involves random partitions. We call it Similarity Analysis. It basically consists of decomposing ...
A method for combining inference across related nonparametric Bayesian models
(WILEY, 2004)
We consider the problem of combining inference in related nonparametric Bayes models. Analogous to parametric hierarchical models, the hierarchical extension formalizes borrowing strength across the related submodels. In ...
Dependent Bayesian nonparametric modeling of compositional data using random Bernstein polynomials
(Institute of Mathematical Statistics, 2022)
We discuss Bayesian nonparametric procedures for the regression analysis of compositional responses, that is, data supported on a multivariate simplex. The procedures are based on a modified class of multivariate Bernstein ...
Semiparametric Bayesian inference for multilevel repeated measurement data
(WILEY, 2007)
We discuss inference for data with repeated measurements at multiple levels. The motivating example is data with blood counts from cancer patients undergoing multiple cycles of chemotherapy, with days nested within cycles. ...
Nonparametric Bayesian modelling using skewed Dirichlet processes
(ELSEVIER, 2009)
We introduce a new class of discrete random probability measures that extend the definition of Dirichlet process (DP) by explicitly incorporating skewness. The asymmetry is controlled by a single parameter in such a way ...
BAYESIAN SEMIPARAMETRIC INFERENCE FOR MULTIVARIATE DOUBLY-INTERVAL-CENSORED DATA
(INST MATHEMATICAL STATISTICS, 2010)
Based on a data set obtained in a dental longitudinal study, conducted in Flanders (Belgium), the joint time to caries distribution of permanent first molars was modeled as a function of covariates. This involves an analysis ...
Computational aspects of nonparametric Bayesian analysis with applications to the modeling of multiple binary sequences
(AMER STATISTICAL ASSOC, 2000)
We consider Markov mixture models for multiple longitudinal binary sequences. Prior uncertainty in the mixing distribution is characterized by a Dirichlet process centered on a matrix beta measure. We use this setting to ...