scholarly journals Maximum Entropy and Bayesian Inference for the Monty Hall Problem

2016 ◽  
Vol 04 (07) ◽  
pp. 1222-1230
Author(s):  
Jennifer L. Wang ◽  
Tina Tran ◽  
Fisseha Abebe
2019 ◽  
Vol 33 (3) ◽  
pp. 144-162 ◽  
Author(s):  
Joshua B. Miller ◽  
Adam Sanjurjo

We show how classic conditional probability puzzles, such as the Monty Hall problem, are intimately related to the recently discovered hot hand selection bias. We explain the connection by way of the principle of restricted choice, an intuitive inferential rule from the card game bridge, which we show is naturally quantified as the updating factor in the odds form of Bayes’s rule. We illustrate how, just as the experimental subject fails to use available information to update correctly when choosing a door in the Monty Hall problem, researchers may neglect analogous information when designing experiments, analyzing data, and interpreting results.


2005 ◽  
Vol 08 (01) ◽  
pp. 1-12 ◽  
Author(s):  
FRANCISCO VENEGAS-MARTÍNEZ

This paper develops a Bayesian model for pricing derivative securities with prior information on volatility. Prior information is given in terms of expected values of levels and rates of precision: the inverse of variance. We provide several approximate formulas, for valuing European call options, on the basis of asymptotic and polynomial approximations of Bessel functions.


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