5 papers
Bayesian mixture modeling using a mixture of finite mixtures with normalized inverse Gaussian weights
Fumiya Iwashige, Shintaro Hashimoto
In Bayesian inference for mixture models with an unknown number of components, a finite mixture model is usually employed that assumes prior distributions for mixing weights and th…
Global-local shrinkage priors for modeling random effects in multivariate spatial small area estimation
Shushi Nishina, Takahiro Onizuka, Shintaro Hashimoto
Small area estimation (SAE) plays a central role in survey statistics and epidemiology, providing reliable estimates for domains with limited sample sizes. The multivariate Fay-Her…
On Misspecified Error Distributions in Bayesian Functional Clustering: Consequences and Remedies
Fumiya Iwashige, Tomoya Wakayama, Shonosuke Sugasawa +1
Nonparametric Bayesian approaches provide a flexible framework for clustering without pre-specifying the number of groups, yet they are well known to overestimate the number of clu…
Robust Bayesian Inference for Censored Survival Models
Yasuyuki Hamura, Takahiro Onizuka, Shintaro Hashimoto +1
This paper proposes a robust Bayesian accelerated failure time model for censored survival data. We develop a new family of life-time distributions using a scale mixture of the gen…
Robust Bayesian graphical modeling using -divergence
Takahiro Onizuka, Shintaro Hashimoto
Gaussian graphical model is one of the powerful tools to analyze conditional independence between two variables for multivariate Gaussian-distributed observations. When the dimensi…