Merlise A Clyde

 

 


 

Dr. Merlise Clyde is Professor of Statistical Science at Duke University and has served as Chair of the Department of Statistical Science at Duke since 2013. She received her PhD in 1993 from the University of Minnesota and joined the faculty at the Institute of Statistics and Decision Sciences (now the Department of Statistical Sciences) at Duke University in the fall of 1993. Professor Clyde is a past President of the International Society of Bayesian Analysis (ISBA), and is an elected Fellow of ISBA and the American Statistical Association. Professor Clyde's research focuses on Bayesian solutions to the related problems of feature/variable selection, model selection and prediction using an ensemble of models to account for model uncertainty using Bayesian Model Averaging, with an emphasis on prior choice and computation. She has developed R packages in conjunction to support articles, including BAS, Bayesian Adaptive Sampling for Bayesian Model Averaging. Her work is inspired by applications in environmental health, chemistry, genomics, neuroscience and astronomy, among others.




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Dec 12th 2016

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm.

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