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Combining experts' opinions using a normal‐wishart model
Author(s) -
Wiper Michael P.,
French Simon
Publication year - 1995
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980140103
Subject(s) - quantile , wishart distribution , decision maker , econometrics , bayesian probability , transformation (genetics) , computer science , normal distribution , mathematics , statistics , operations research , multivariate statistics , biochemistry , chemistry , gene
This paper examines how a Bayesian decision maker might update her distributions for continuous variables X i , i=1, 2 , …, upon hearing experts' forecasts expressed as quantiles. To utilize the relationship between the decision maker and experts, and to avoid problems associated with different scales and ranges of the variables, we assume that the decision maker transforms the experts' quantiles in terms of her own prior distribution for each X i . A model using such a transformation is presented and its properties are examined.