4 papers
On MCMC mixing for predictive inference under unidentified transformation models
Chong Zhong, Jin Yang, Junshan Shen +2
Reliable Bayesian predictive inference has long been an open problem under unidentified transformation models, since the Markov Chain Monte Carlo (MCMC) chains of posterior predict…
Non-segmental Bayesian Detection of Multiple Change-points
Chong Zhong, Zhihua Ma, Xu Zhang +1
We propose an original and general NOn-SEgmental (NOSE) approach for the detection of multiple change-points. NOSE identifies change-points by the non-negligibility of posterior es…
Bayesian prediction via nonparametric transformation models
Chong Zhong, Jin Yang, Junshan Shen +2
This article tackles the old problem of prediction via a nonparametric transformation model (NTM) in a new Bayesian way. Estimation of NTMs is known challenging due to model uniden…
Dependent Dirichlet Processes for Analysis of a Generalized Shared Frailty Model
Chong Zhong, Zhihua Ma, Junshan Shen +1
Bayesian paradigm takes advantage of well fitting complicated survival models and feasible computing in survival analysis owing to the superiority in tackling the complex censoring…