Perfect Sampling of the Posterior in the Hierarchical Pitman-Yor Process [0.03%]
分层Pitman-Yor过程中后验的完美采样
Sergio Bacallado,Stefano Favaro,Samuel Power et al.
Sergio Bacallado et al.
The predictive probabilities of the hierarchical Pitman-Yor process are approximated through Monte Carlo algorithms that exploits the Chinese Restaurant Franchise (CRF) representation. However, in order to simulate the posterior distributio...
Andrew A Manderson,Robert J B Goudie
Andrew A Manderson
A challenge for practitioners of Bayesian inference is specifying a model that incorporates multiple relevant, heterogeneous data sets. It may be easier to instead specify distinct submodels for each source of data, then join the submodels ...
Cheng Zhang,Babak Shahbaba,Hongkai Zhao
Cheng Zhang
Traditionally, the field of computational Bayesian statistics has been divided into two main subfields: variational methods and Markov chain Monte Carlo (MCMC). In recent years, however, several methods have been proposed based on combining...
Generalized Geographically Weighted Regression Model within a Modularized Bayesian Framework [0.03%]
模块化贝叶斯框架下的广义地理加权回归模型
Yang Liu,Robert J B Goudie
Yang Liu
Geographically weighted regression (GWR) models handle geographical dependence through a spatially varying coefficient model and have been widely used in applied science, but its general Bayesian extension is unclear because it involves a w...
Jonathan H Huggins,Jeffrey W Miller
Jonathan H Huggins
Bayesian model selection is premised on the assumption that the data are generated from one of the postulated models. However, in many applications, all of these models are incorrect (that is, there is misspecification). When the models are...
Robust Adaptive Incorporation of Historical Control Data in a Randomized Trial of External Cooling to Treat Septic Shock [0.03%]
历史对照数据在随机试验中针对Septic Shock进行外部冷却治疗的自适应稳健结合
Thomas A Murray,Peter F Thall,Frederique Schortgen et al.
Thomas A Murray et al.
This paper proposes randomized controlled clinical trial design to evaluate external cooling as a means to control fever and thereby reduce mortality in patients with septic shock. The trial will include concurrent external cooling and cont...
Scalable Approximate Bayesian Computation for Growing Network Models via Extrapolated and Sampled Summaries [0.03%]
基于插补和采样摘要的可扩展近似贝叶斯推断在增长网络模型中的应用
Louis Raynal,Sixing Chen,Antonietta Mira et al.
Louis Raynal et al.
Approximate Bayesian computation (ABC) is a simulation-based likelihood-free method applicable to both model selection and parameter estimation. ABC parameter estimation requires the ability to forward simulate datasets from a candidate mod...
Federico Camerlenghi,David B Dunson,Antonio Lijoi et al.
Federico Camerlenghi et al.
Discrete random structures are important tools in Bayesian nonparametrics and the resulting models have proven effective in density estimation, clustering, topic modeling and prediction, among others. In this paper, we consider nested proce...
Centered Partition Processes: Informative Priors for Clustering (with Discussion) [0.03%]
中心化分区过程：聚类的先验信息
Sally Paganin,Amy H Herring,Andrew F Olshan et al.
Sally Paganin et al.
There is a very rich literature proposing Bayesian approaches for clustering starting with a prior probability distribution on partitions. Most approaches assume exchangeability, leading to simple representations in terms of Exchangeable Pa...
Improving multilevel regression and poststratification with structured priors [0.03%]
基于结构先验的多层回归和后分层的改进
Yuxiang Gao,Lauren Kennedy,Daniel Simpson et al.
Yuxiang Gao et al.
A central theme in the field of survey statistics is estimating population-level quantities through data coming from potentially non-representative samples of the population. Multilevel regression and poststratification (MRP), a model-based...