Understanding Prior Probability in Bayesian Statistics

Learn how prior probability informs economic theory and decision-making in Bayesian statistics. Understand its role before collecting new data.
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 ...
JSTOR Daily

Bayesian MAP estimation using Gaussian and diffused-gamma prior

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 46, No. 3 (September/septembre 2018), pp. 399-415 (17 pages) For sparse and high-dimensional data analysis, a valid ...
JSTOR Daily

Smooth Empirical Bayes Estimation for One-Parameter Discrete Distributions

A study is made of the simple empirical Bayes estimators proposed by Robbins (1956). These estimators are compared with `best' conventional estimators in terms of ...
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 ...
How-To Geek on MSN

This one change made my Home Assistant automations far more accurate

The beauty of Bayesian sensors is that they can make your Home Assistant automations much more accurate. If your cat does sometimes set off your motion sensor, for example, you can't rely on the ...
ascopubs.org

Interpreting Trial Results in Light of Conflicting Evidence: A Bayesian Analysis of Adjuvant Chemotherapy for Non–Small-Cell Lung Cancer

Randomized Phase II Study of Gefitinib Compared With Placebo in Chemotherapy-Naive Patients With Advanced Non–Small-Cell Lung Cancer and Poor Performance Status When successive randomized trials ...