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Portable Network Graphic  |  1994-04-29  |  85KB  |  816x1056  |  8-bit (256 colors)
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OCR: Bayes Plot forEffect Screening A Bayes plot assumes that the estimates are a mixture from two distributions as follows: Some portion the effects are assumed to come from pure random noise with small variance The remaining terms are assumed to come from a contaminating distribution that has variance K times larger. The prior probability given an effect is the chance you give that effec of being non-zero, (or being in the contaminating distribution) These priors are usually set to equal values for each effect, and commonly recommended prior probability value The contaminatior coefficient often set at 10 which says the contaminating distributic has a variance that is 10 times the error variance. The Bayes plot IC done with respect to normalized estimates those wh have been transformed to be u ...