Premium
Informative priors in Bayesian inference and computation
Author(s) -
Golchi Shirin
Publication year - 2019
Publication title -
statistical analysis and data mining: the asa data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.381
H-Index - 33
eISSN - 1932-1872
pISSN - 1932-1864
DOI - 10.1002/sam.11371
Subject(s) - prior probability , inference , computer science , bayesian inference , prior information , bayesian probability , machine learning , artificial intelligence , computation , algorithm
The use of prior distributions is often a controversial topic in Bayesian inference. Informative priors are often avoided at all costs. However, when prior information is available, informative priors are appropriate means of introducing this information into the model. Furthermore, informative priors, when used properly and creatively, can provide solutions to computational issues and improve inference. Through 3 examples with different applications, we demonstrate the importance and utilities of informative priors in incorporating external information into the model and overcoming computational difficulties.