'Informative prior' diaporamas de présentation

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About priors

About priors. Greg Francis. PSY 626: Bayesian Statistics for Psychological Science Fall 2018 Purdue University. Levels of priors. Flat prior: You know nothing, often improper Super-vague but proper: N(0,1000000) Weakly informative prior: N(0, 10) Generic weakly informative prior: N(0,1)

354 views • 35 slides

About priors

About priors. Greg Francis. PSY 626: Bayesian Statistics for Psychological Science Fall 2018 Purdue University. Levels of priors. Flat prior: You know nothing, often improper Super-vague but proper: N(0,1000000) Weakly informative prior: N(0, 10) Generic weakly informative prior: N(0,1)

353 views • 35 slides

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Chantal D. Larose

Evaluating Diagnostic Accuracy of Prostate Cancer Using Bayesian Analysis Part of an Undergraduate Research course. Chantal D. Larose. Overview. Introduction Three Ingredients to the Analysis ROC Curves Bayesian Analysis Results Discussion. Introduction.

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OPC

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Expert Prior Elicitation in Bayesian Adaptive Survey Design: Two Case Studies

Expert Prior Elicitation in Bayesian Adaptive Survey Design: Two Case Studies. , ,. Outline. Why Bayesian analysis Prior Elicitation General Methodology Similarity Criteria Criteria Importance Modelling Application Energy Survey 2018 SILC Survey 2016 Conclusion. 1.

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Confidence Intervals for Capture-Recapture Data With Matching

Confidence Intervals for Capture-Recapture Data With Matching. Stephen Sharp, National Records of Scotland. The Problem (i). You have undertaken a (presumably imperfect) enumeration of a given population. You then undertaken a second (also presumably imperfect) coverage survey .

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First, a question

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