Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

The main focus of this short course will be the Bayesian aspect of it. That means this is a slightly more advanced course requiring some knowledge of basic probability, regression methods, and the R ...

In many applications, interest focuses on assessing the relationship between a predictor and a multivariate outcome variable, and there may be prior knowledge about the shape of the regression curves.

Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols Journal of the ...

We’ll discuss some basic concepts and vocabulary in Bayesian statistics such as the likelihood, prior and posterior distributions, and how they relate to Bayes’ Rule. R statistical software will be ...