Chris C. Holmes

Overview

Chris C. Holmes is a statistician at the University of Oxford (Department of Statistics). His research spans Bayesian computation, machine learning, and genomics, with contributions to auxiliary variable MCMC methods for generalised linear models.

Key Contributions

• Holmes-Held (2006): Exact auxiliary variable Gibbs sampler for Bayesian logistic regression via the Kolmogorov-Smirnov scale mixture of normals; joint probit update scheme reducing autocorrelation ~2×; extension to multinomial logistic regression and variable selection with Bayes-factor acceptance.

Related

• Bayesian Logistic Regression
• Data Augmentation
• Binary Probit
• Auxiliary Variable Sampler
• Holmes-Held (2006)
• Leonhard Held