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• W2096388500 abstract "In this paper we propose a simple adaptive Metropolis-withinGibbs algorithm attempting to study directions on which the Metropolis algorithm can be ran ∞exibly. The algorithm avoids the wasting moves in wrong directions by proposals from the full dimensional adaptive Metropolis algorithm. We also prove its ergodicity, and test it on a Gaussian Needle example and a real-life Case-Cohort study with competing risks. For the Cohort study, we describe an extensive version of Competing Risks Regression model, deflne censor variables for competing risks, and then apply the algorithm to estimate coe‐cients based on the posterior distribution." @default.
• W2096388500 created "2016-06-24" @default.
• W2096388500 creator A5080693761 @default.
• W2096388500 date "2009-01-01" @default.
• W2096388500 modified "2023-09-27" @default.
• W2096388500 title "An Adaptive Directional Metropolis-within-Gibbs algorithm" @default.
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