insider.si.edu

Statistical rethinking : a Bayesian course with examples in R and Stan / Richard McElreath, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

SERC copy Purchased with Adopt-a-Book funds. "Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the ...
JSTOR Daily

Beta generalized distributions and related exponentiated models: A Bayesian approach

Brazilian Journal of Probability and Statistics, Vol. 27, No. 1 (February 2013), pp. 1-19 (19 pages) We introduce a Bayesian analysis for beta generalized distributions and related exponentiated ...
JSTOR Daily

Bayesian Analysis of Proportional Hazards Models Built from Monotone Functions

We consider the usual proportional hazards model in the case where the baseline hazard, the covariate link, and the covariate coefficients are all unknown. Both the baseline hazard and the covariate ...
ascopubs.org

Bayesian Approaches to Subgroup Analysis and Related Adaptive Clinical Trial Designs

We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...
esa.org

Statistical Methods Seminar Series: Bayesian Stable Isotope Mixing Models and the MixSIAR R package

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are ...
Diginomica

Can Bayesian Networks provide answers when Machine Learning comes up short? It's a question of probabilities

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...