External links
- Home page
- Merlise A. Clyde publications indexed by Google Scholar
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Merlise Aycock Clyde | |
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| Alma mater | |
| Scientific career | |
| Fields | Statistics |
| Institutions | Duke University |
| Thesis | Bayesian Optimal Designs for Approximate Normality (1994) |
| Doctoral advisor | Kathryn Chaloner |
Merlise Aycock Clyde is an American statistician known for her work in model averaging for Bayesian statistics. She is a professor of Statistical Science and immediate past chair of the Department of Statistical Science at Duke University. [1] She was president of the International Society for Bayesian Analysis (ISBA) in 2013, [2] and chair of the Section on Bayesian Statistical Science of the American Statistical Association for 2018. [3]
Clyde graduated from Oregon State University in 1985 with a Bachelor of Science in Forestry. She earned two master's degrees, one from the University of Alberta in 1986 in Forest Biometrics and another from the University of California, Riverside in 1988 in Statistics, before completing her Ph.D. at the University of Minnesota in 1993 in Statistics. [1] Her dissertation, supervised by Kathryn Chaloner, was Bayesian Optimal Designs for Approximate Normality [4] , which received the Savage Award for outstanding dissertation in Bayesian econometrics and statistics in 1994. [5]
Clyde is a fellow of the American Statistical Association, of the International Society for Bayesian Analysis, [1] and of the Institute of Mathematical Statistics. [6] She was one of two winners of the Zellner Medal of the ISBA in 2016 "for their outstanding service to ISBA". [7]
Sylvia Therese Richardson is a French/British Bayesian statistician and is currently Professor of Biostatistics and Director of the MRC Biostatistics Unit at the University of Cambridge. In 2021 she became the president of the Royal Statistical Society for the 2021–22 year.
Sudipto Banerjee is an Indian-American statistician best known for his work on Bayesian hierarchical modeling and inference for spatial data analysis. He is Professor of Biostatistics and Senior Associate Dean in the School of Public Health at the University of California, Los Angeles. He served as the Chair of the Department of Biostatistics at UCLA from 2014 through 2023. He served as the elected President of the International Society for Bayesian Analysis in 2022.
Kerrie Mengersen is an Australian statistician, distinguished Professor of Statistics at Queensland University of Technology, and 2024 winner of the Ruby Payne-Scott Medal from the Australian Academy of Science.
Alan Enoch Gelfand is an American statistician, and is currently the James B. Duke Professor of Statistics and Decision Sciences at Duke University. Gelfand’s research includes substantial contributions to the fields of Bayesian statistics, spatial statistics and hierarchical modeling.
Marie Davidian is an American biostatistician known for her work in longitudinal data analysis and precision medicine. She is the J. Stuart Hunter Distinguished Professor of Statistics at North Carolina State University. She was president of the American Statistical Association for 2013.
Lynn Kuo is a professor of statistics at the University of Connecticut known for her work on Bayesian inference in phylogeny. With Ming-Hui Chen and Paul O. Lewis, she is the author of Bayesian Phylogenetics: Methods, Algorithms, and Applications.
Marina Vannucci is an Italian statistician, the Noah Harding Professor and Chair of Statistics at Rice University, the past president of the International Society for Bayesian Analysis, and the former editor-in-chief of Bayesian Analysis. Topics in her research include wavelets, feature selection, and cluster analysis in Bayesian statistics.
Amy Helen Herring is an American biostatistician interested in longitudinal data and reproductive health. Formerly the Carol Remmer Angle Distinguished Professor of Children's Environmental Health at the University of North Carolina at Chapel Hill, she is now Sara & Charles Ayres Distinguished Professor in the Department of Statistical Science, Global Health Institute, and Department of Biostatistics & Bioinformatics of Duke University.
Judith Rousseau is a Bayesian statistician who studies frequentist properties of Bayesian methods. She is a professor of statistics at the University of Oxford, a Fellow of Jesus College, Oxford, a Fellow of the Institute of Mathematical Statistics, and a Fellow of the International Society for Bayesian Analysis.
Sonia Petrone is an Italian mathematical statistician, known for her work in Bayesian statistics, including use of Bernstein polynomials for nonparametric methods in Bayesian statistics.[RBP][BDE][CPP] With Patrizia Campagnoli and Giovanni Petris she is the author of the book Dynamic Linear Models with R .[DLM]
Raquel Prado is a Venezuelan Bayesian statistician. She is a professor of statistics in the Jack Baskin School of Engineering of the University of California, Santa Cruz, and has been elected president of the International Society for Bayesian Analysis for the 2019 term.
Alexandra M. (Alex) Schmidt is a Brazilian biostatistician and epidemiologist who works as an associate professor of biostatistics at McGill University in Canada. She is known for her research on spatiotemporal and multivariate statistics and their applications in environmental statistics.
Fabrizio Ruggeri is an Italian statistician. He is Research Director at the National Research Council Istituto di matematica applicata e tecnologie informatiche (CNR-IMATI) in Milan, Italy. His work focusses on Bayesian methods, specifically robustness and stochastic process inference. He has done innovative work on sensitivity of Bayesian methods and incompletely specified priors. He has worked on Bayesian wavelet methods, and on a vast variety of applications to industrial problems. His publications include well over 150 refereed papers and book chapters, as well as five books.
Elena Aleksandrovna Erosheva is a Russian-American statistician and social scientist whose research applies Bayesian hierarchical modeling and latent variable models to problems in the social, behavioral, and health sciences. She is a professor at the University of Washington, appointed jointly in the Department of Statistics and the School of Social Work, and the director of the university's Center for Statistics and the Social Sciences.
Susan Mary Paddock is an American statistician whose publications have included work on nonparametric Bayesian inference, substance abuse, and the safety of autonomous vehicles.
Christian P. Robert is a French statistician, specializing in Bayesian statistics and Monte Carlo methods.
Antonietta Mira is an Italian computational statistician whose research involves the application of Markov chain Monte Carlo methods to Bayesian inference. She is a professor of statistics in the Faculty of Economics and Institute of Computational Science at the Università della Svizzera italiana in Lugano, Switzerland, and professor of statistics in the University of Insubria in Italy.
Mike West is an English and American statistician. West works primarily in the field of Bayesian statistics, with research contributions ranging from theory to applied research in areas including finance, commerce, macroeconomics, climatology, engineering, genomics and other areas of biology. Since 1999, West has been the Arts & Sciences Distinguished Professor of Statistics & Decision Sciences in the Department of Statistical Science at Duke University.
Steve MacEachern is an American Statistician. MacEachern is a Distinguished Arts & Sciences Professor of Statistics at the Ohio State University. He received his B.A. in Mathematics from Carleton College in 1982 and his Ph.D. in Statistics from the University of Minnesota in 1988. His doctoral work focused on nonparametric Bayesian methods under the guidance of Don Berry. MacEachern joined the faculty at Ohio State in 1988 and has been a member of the Department of Statistics ever since. He has a courtesy appointment as a Professor in the Department of Psychology. He is best known for Bayesian modeling and computation, with a particular emphasis on dependent Dirichlet processes. He has published extensively in leading statistical journals, and his work has had a significant impact on the field.
Xinyi Xu is a Chinese-American statistician and a professor of statistics at Ohio State University. Her research includes work on high-dimensional Bayesian hierarchical modeling, model selection, and density estimation.
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