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stat.ME2025
Location--Scale Calibration for Generalized Posterior
Shu Tamano, Yui Tomo
General Bayesian updating replaces the likelihood with a loss scaled by a learning rate, but posterior uncertainty can depend sharply on that scale. We propose a simple post-proces…
stat.ME2025
Efficient Gibbs Sampling in Cox Regression Models Using Composite Partial Likelihood and Pólya-Gamma Augmentation
Shu Tamano, Yui Tomo
The Cox regression models and their Bayesian extensions are widely used for time-to-event analysis. However, standard Bayesian approaches typically require baseline hazard modeling…