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Bayesian Inference for the Ratio of the Means of Two Normal Populations with Unequal Variances
Author(s) -
Mendoza M.,
GutiérrezPeña E.
Publication year - 1999
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/(sici)1521-4036(199905)41:2<133::aid-bimj133>3.0.co;2-5
Subject(s) - frequentist inference , homoscedasticity , bayesian probability , mathematics , inference , bayes factor , statistics , bayesian inference , econometrics , bayes' theorem , contrast (vision) , frequentist probability , computer science , artificial intelligence , heteroscedasticity
The problem of making inferences about the ratio of two normal means has been addressed, both from the frequentist and Bayesian perspectives, by several authors. Most of this work is concerned with the homoscedastic case. In contrast, the situation where the variances are not equal has received little attention. C ox (1985) deals, within the frequentist framework, with a model where the variances are related to the means. His results are mainly based on Fieller's theorem whose drawbacks are well known. In this paper we present a Bayesian analysis of this model and discuss some related problems. An agronomical example is used throughout to illustrate the methods.