Probabilities as Similarity-Weighted Frequencies

Antoine Billot; Itzhak Gilboa; Dov Samet; David Schmeidler

doi:10.1142/9789814366182_0007

Probabilities as Similarity-Weighted Frequencies

Antoine Billot, Itzhak Gilboa, Dov Samet, David Schmeidler

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

A decision maker is asked to express her beliefs by assigning probabilities to certain possible states. We focus on the relationship between her database and her beliefs. We show that, if beliefs given a union of two databases are a convex combination of beliefs given each of the databases, the belief formation process follows a simple formula: beliefs are a similarity-weighted average of the beliefs induced by each past case.

Original language	English
Title of host publication	Case-Based Predictions
Subtitle of host publication	An Axiomatic Approach to Prediction, Classification and Statistical Learning
Publisher	Taylor and Francis
Pages	169-184
Number of pages	16
ISBN (Electronic)	9789814366182
ISBN (Print)	981436617X, 9789814366175
DOIs	https://doi.org/10.1142/9789814366182_0007
State	Published - 1 Jan 2012

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10.1142/9789814366182_0007

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Probabilities as Similarity-Weighted Frequencies

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