Muller P, Quintana F: Nonparametric Bayesian data analysis. Statistical Science 2004, 19 (1) : 95–110. 10.1214/088342304000000017Müller P, Quintana F (2004) Nonparametric Bayesian data analysis. Stat Sci 19: 95–110Muller, P., and Quintana, F. A. (2004), “Nonparametric Bayesian Data ...
Meanwhile, the inference of the model depends on the efficient online variational Bayesian approach, which enhances the information exchange between the whole and the part to a certain extent and applies to scalable datasets. The experiments on the scene database indicate that the novel clustering ...
Under the Bayesian framework, a detouring approach for spectral estimation is proposed for analyzing irregularly spaced data. The detouring process is accomplished by three steps: (1) normalizing the data in some sense on frequency domain by a time-scale change, (2) estimating the spectral density...
Bayesian non﹑arametric hidden Markov models with applications in genomics O, Roberts GO, Holmes C: Bayesian nonparametric hidden Markov models with application to the analysis of copy number variation in mammalian genomes. J... C Yau,O Papaspiliopoulos,GO Roberts,... - 《Journal of the Royal...
Luo S. A Bayesian approach to joint analysis of multivariate longitudinal data and parametric accelerated failure time. Stat. Med. 2014; 33:580-594... S Luo - 《Statistics in Medicine》 被引量: 23发表: 2013年 Nonparametric survival regression using the beta-Stacy process accelerated failure tim...
Bayesian nonparametrics in NIMBLE: Nonparametric random effects Overview NIMBLE is a hierarchical modeling package that uses nearly the same language for model specification as the popular MCMC packages WinBUGS, OpenBUGS and JAGS, while making the modeli
Bayesian methodsFunctional data analysisMixed modelsModel averagingNonparametric regressionProteomicsWaveletsIncreasingly, scientific studies yield functional data, in ... JS Morris,RJ Carroll - 《Journal of the Royal Statistical Society》 被引量: 644发表: 2006年 Empirical Bayes Estimation in Wavelet Nonpara...
To tackle this problem, we present a novel ASC feature extraction algorithm for SAR targets based on Levy random fields in a nonparametric Bayesian framework. Specifically, Levy random fields, yielding a natural sparse representation of the unknown ASC model, are introduced to construct prior ...
Results Utilizing nonparametric Bayesian clustering followed by hypothesis testing, we have developed a novel statistical approach to identify bipolar methylated genomic regions in bisulfite sequencing data. Simulation studies demonstrate that the proposed method achieves good performance in terms of specificity...
Bayesian nonparametrics; Epidemiologic studies; Robustness Summary A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locatio...