File:Bayes-rule-for-Gaussians.jpg

Bayes-rule-for-Gaussians.jpg (600 × 488 pixels, file size: 44 KB, MIME type: image/jpeg)

Summary

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English: Bayes rule for Gaussians. For the prior p(x) (blue) m0=20, λ0=1 and the likelihood p(y∣x) (red) mD=25 and λD=3 , the posterior p(x∣y) (magenta) shows the posterior distribution with m=23.75 and λ=4 . The posterior is closer to the likelihood than the prior because the likelihood has higher precision. Bayes rule for Gaussians has been used to explain many behaviours from sensory integration to collective decision making.
Date
Source William Penny. "Bayesian Models of Brain and Behaviour", ISRN Biomathematics doi:10.5402/2012/785791
Author William Penny
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24 September 2012

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current16:13, 14 February 2020Thumbnail for version as of 16:13, 14 February 2020600 × 488 (44 KB)JoramSochUploaded by the NOA Upload Tool

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