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Linear combination of forecasts with an intercept: A bayesian approach
Author(s) -
Bordley Robert F.
Publication year - 1986
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.3980050405
Subject(s) - bayesian probability , decision maker , computer science , consensus forecast , term (time) , econometrics , statistics , mathematics , artificial intelligence , operations research , physics , quantum mechanics
The standard approach to combining n expert forecasts involves taking a weighted average. Granger and Ramanathan proposed introducing an intercept term and unnormalized weights. This paper deduces their proposal from Bayesian principles. We find that their formula is equivalent to taking a weighted average of the n expert forecasts plus the decision‐maker's prior forecast.
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