Bayesian One- Way Repeated Measurements Model as a Mixed Model
Abstract
In the Bayesian approach to inference, all unknown quantities contained in a probability model for the observed data are treated as random variables. Specifically, the fixed but unknown parameters are viewed as random variables under the Bayesian approach. In this paper, Bayesian approach is employed to making inferences on the one- way repeated measurements model as mixed model , and we prove some theorems about posterior.
Keywords: Mixed models, One- way repeated measurements model , Bayesian inference, Prior density, Posterior density.
To list your conference here. Please contact the administrator of this platform.
Paper submission email: MTM@iiste.org
ISSN (Paper)2224-5804 ISSN (Online)2225-0522
Please add our address "contact@iiste.org" into your email contact list.
This journal follows ISO 9001 management standard and licensed under a Creative Commons Attribution 3.0 License.
Copyright © www.iiste.org