Model search in probit regression is often conducted by simultaneously exploring the model and parameter space, using a reversible jump MCMC sampler. Standard samplers often have low model acceptance ...

CATALOG DESCRIPTION: Fundamental and advanced topics in statistical pattern recognition including Bayesian decision theory, Maximum-likelihood and Bayesian estimation, Nonparametric density estimation ...

Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 42, No. 4, Special Issue: Conference on Practical Bayesian Statistics, 1992 (1993), pp. 385-397 (13 pages) Bayesian ideas ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Data analytics (DA) is a science that combines data mining, machine learning, and statistics. DA examines raw data with the purpose of discovering useful information ...

A common misconception about Bayesian statistics is that it mainly involves incorporating personal prior beliefs or subjective opinions. While priors do play a role, the core strength of Bayesian ...

This course is available on the BSc in Accounting and Finance. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.

Veronika Rockova, professor of econometrics and statistics and the James S. Kemper Foundation Faculty Fellow, has won the 2024 COPSS Presidents’ Award for her outstanding contributions to the ...