1,721,148 research outputs found
A simple procedure calculating the generalized Stieltjes transform of the mean of a Dirichlet process
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Bayesian and conditional frequentist testing of a parametric model versus nonparametric alternatives
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Model-Based Clustering of Spatial Time Series Through the BayesMix library
No full textIn this work, we consider time series of daily concentrations of PM10 monitored in Lombardia and Emilia-Romagna during 2018. With the aim of clustering those spatial time series, we propose a Bayesian nonparametric mixture of autoregressive processes and assume as mixing measure a spatial product partition model. We focus on the implementation of this model into BayesMix, a new C++ library for Bayesian inference on nonparametric mixture models via Markov Chain Monte Carlo. The main feature of this library is its extensibility, which guarantees a seamless integration of new classes of mixture models, like the one we introduce in this paper, without compromising efficiency
Nonparametric Bayesian mixture modelling for failure time data
No full textWe fit a Bayesian semiparametric accelerated failure time
mixed-effects model to a classical Kevlar fibre lifetime dataset (with censoring). The error is a shape-scale mixture of Weibull densities, mixed by a normalized generalized gamma random measure, encompassing the Dirichlet process. We implement an MCMC scheme, obtaining
posterior credibility intervals for the predictive distributions and
for the quantiles of the failure times under different stress levels. Random spool effects are taken up by the nonparametric mixture, where every component accounts for a different spool. Compared to previous analyses, we obtain narrower credibility intervals and a better fit to the data
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