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Surviving fully Bayesian nonparametric regression models
(Oxford University Press, 2013)
This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability distributions. It begins by reviewing ...
A Bayesian approach to hybrid splines non-parametric regression
(Taylor & Francis LtdAbingdonInglaterra, 2002)
Efficient bayesian methods for mixture models with genetic applications
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2016-12-14)
We propose Bayesian methods for selecting and estimating di erent types of mixture models which are widely used in Genetics and Molecular Biology. We speci cally propose data-driven selection and estimation methods for a ...
Bayesian inference for longitudinal data with nonparametrics random effects
(2014)
We consider inference for longitudinal data based on mixed-effects models with a non-parametric Bayesian prior on the treatment effect.
The proposed non-parametric Bayesian prior is a random partition model with a regression ...
Bayesian inference for longitudinal data with non-parametric treatment effects
(2014)
We consider inference for longitudinal data based on mixed-effects models with a non-parametric Bayesian prior on the treatment effect.
The proposed non-parametric Bayesian prior is a random partition model with a regression ...
Random partition models with regression on covariates
(ELSEVIER SCIENCE BV, 2010)
Many recent applications of nonparametric Bayesian inference use random partition models, i.e. probability models for clustering a set of experimental units. We review the popular basic constructions. We then focus on an ...
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. ...
Optimal sampling for repeated binary measurements
(CANADIAN JOURNAL STATISTICS, 2004)
The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling ...