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Merlise Clyde

Professor of Statistical Science
Statistical Science
Duke Box 90251, Durham, NC 27708-0251
223E Old Chem Bldg, Box 90251, Durham, NC 27708

Overview


Model uncertainty and choice in prediction and variable selection problems for linear, generalized linear models and multivariate models. Bayesian Model Averaging. Prior distributions for model selection and model averaging. Wavelets and adaptive kernel non-parametric function estimation. Spatial statistics. Experimental design for nonlinear models. Applications in proteomics, bioinformatics, astro-statistics, air pollution and health effects, and environmental sciences.

Office Hours


Fall 2023: 

DGS Office Hours:  Wed 1:30-2:30

STA 702:  Mon 9:00am-10am and Thur 1:30-2:30 pm


or by appointment - send an outlook invite if there are no conflicts!

Current Appointments & Affiliations


Professor of Statistical Science · 2011 - Present Statistical Science, Trinity College of Arts & Sciences
Chair of the Department of Statistical Science · 2025 - Present Statistical Science, Trinity College of Arts & Sciences

In the News


Published March 1, 2023
Celebrating Women in Statistics and Data Science
Published January 12, 2023
Building Hope for Racial Equity Work at Duke in 2023
Published May 22, 2020
Clyde, Reiter Named Institute of Mathematical Statistics Fellows

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Recent Publications


A tutorial on Bayesian multi-model linear regression with BAS and JASP.

Journal Article Behavior research methods · December 2021 Linear regression analyses commonly involve two consecutive stages of statistical inquiry. In the first stage, a single 'best' model is defined by a specific selection of relevant predictors; in the second stage, the regression coefficients of the winning ... Full text Open Access Cite

Mixtures of g-priors in Generalized Linear Models

Journal Article Journal of the American Statistical Association · December 1, 2018 Featured Publication Mixtures of Zellner's g-priors have been studied extensively in linear models and have been shown to have numerous desirable properties for Bayesian variable selection and model averaging. Several extensions of g-priors to Generalized Linear Models (GLMs) ... Full text Open Access Link to item Cite
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Recent Grants


Quantifying and Communicating Numerical Model Uncertainty

ResearchPrincipal Investigator · Awarded by University of North Carolina - Chapel Hill · 2019 - 2021

Statistical and Applied Mathematical Science Institute

ResearchPrincipal Investigator · Awarded by University of North Carolina - Chapel Hill · 2017 - 2020

Models for Consortium Level Analysis of GxE Interaction in Complex Disease

ResearchCo-Principal Investigator · Awarded by National Institutes of Health · 2012 - 2015

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Education, Training & Certifications


University of Minnesota, Twin Cities · 1993 Ph.D.
University of California, Riverside · 1988 M.S.
University of Alberta (Canada) · 1986 M.S.
Oregon State University · 1985 B.S.