Article1992

Modelling Agent Forecast Distributions

54 citations0/0 files storedJournal of the Royal Statistical Society Series B (Statistical Methodology)

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Forecasting Techniques and Applications Statistical Methods and Bayesian Inference Bayesian Modeling and Causal Inference

Abstract

SUMMARY Problems in the analysis and interpretation of uncertain inferences obtained from individuals, or agents, are considered in the context of forecasting a scalar random quantity. Based on new theoretical results presented by West and Crosse, Bayesian updating is developed for cases in which agents' opinions are provided in terms of full forecast distributions (discrete or continuous), or partial summaries such as forecast means and variances. A particular focus is on problems in which partial agent information is communicated in terms of a few summary probabilities or, alternatively, quantiles of the agent's distribution. Example models highlight the key features of the theory and illustrate applications.

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1984Improved methods of combining forecasts 1982The Combination of Forecasts: A Bayesian Approach

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