Nature

Bayesian Estimation and Maximum Likelihood Methods

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
Investopedia

Understanding Prior Probability in Bayesian Statistics

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
JSTOR Daily

Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective

Selecting a subset of variables for linear models remains an active area of research. This article reviews many of the recent contributions to the Bayesian model selection and shrinkage prior ...
Investopedia

Bayes' Theorem: What It Is, Formula, and Examples

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Electronic Design

Applying Bayes’ Theorem to clinical trials

Over the years, many writers have implied that statistics can provide almost any result that is convenient at the time. Of course, honest practitioners use statistics in an attempt to quantify the ...