Mike West (statistician)

Last updated

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. [1] Since 1999, West has been the Arts & Sciences Distinguished Professor of Statistics & Decision Sciences in the Department of Statistical Science at Duke University. [2]

Contents

Education and career

West earned a BSc in mathematics in 1978, and then PhD in mathematics (Statistics) in 1982, from the University of Nottingham.[ citation needed ] He worked at Warwick University before joining Duke University in 1988, where he became the Director of the Institute of Statistics and Decision Sciences (ISDS) [3] from 1990 to 2001.

West has made significant contributions to Bayesian theory and methods for time series analysis and forecasting. [4] [5] [6] He has also conducted research on non-parametric Bayesian analysis with methodological and applied research that include implementations of Dirichlet process mixture models starting with a paper published in 1995. [7] His research with molecular geneticists and clinical researchers involved developing predictive models for identifying types of breast cancer using gene expression data, [8] [9] contributing to the popularisation of biomarker discovery through gene expression profiling.

West has been a consultant with various companies, banks, government agencies and academic centres, co-founder of a biotech company, and board member of several financial and IT companies. West has also served the international statistics profession in founding roles and as a board member in a number of national and international centres and institutes as well as professional societies.[ citation needed ]

Elected positions & honours

President of the International Society for Bayesian Analysis in 2009–2010.[ citation needed ]

Elected Fellow of the Royal Statistical Society in 1982, of the Institute of Mathematical Statistics in 1993, of the American Statistical Association in 1993, of the International Statistical Institute in 1997, and elected inaugural fellow of the International Society for Bayesian Analysis in 2012.[ citation needed ]

Founding Chair of the International Society for Bayesian Analysis (ISBA) section on Economics, Finance, and Business in 2012-2013 [10]

Chair of the American Statistical Association section on Bayesian Statistical Science in 2010.[ citation needed ]

Books

Selected awards & recognition

Related Research Articles

Bayesian probability is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification of a personal belief.

<span class="mw-page-title-main">Statistical inference</span> Process of using data analysis

Statistical inference is the process of using data analysis to infer properties of an underlying distribution of probability. Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population.

Michael Irwin Jordan is an American scientist, professor at the University of California, Berkeley and researcher in machine learning, statistics, and artificial intelligence.

<span class="mw-page-title-main">Philip Dawid</span> British statistician

Alexander Philip Dawid is Emeritus Professor of Statistics of the University of Cambridge, and a Fellow of Darwin College, Cambridge. He is a leading proponent of Bayesian statistics.

<span class="mw-page-title-main">George E. P. Box</span> British statistician

George Edward Pelham Box was a British statistician, who worked in the areas of quality control, time-series analysis, design of experiments, and Bayesian inference. He has been called "one of the great statistical minds of the 20th century".

Dennis Victor Lindley was an English statistician, decision theorist and leading advocate of Bayesian statistics.

Model selection is the task of selecting a model from among various candidates on the basis of performance criterion to choose the best one. In the context of machine learning and more generally statistical analysis, this may be the selection of a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is well-suited to the problem of model selection. Given candidate models of similar predictive or explanatory power, the simplest model is most likely to be the best choice.

<span class="mw-page-title-main">Hirotugu Akaike</span> Japanese statistician

Hirotsugu Akaike was a Japanese statistician. In the early 1970s, he formulated the Akaike information criterion (AIC). AIC is now widely used for model selection, which is commonly the most difficult aspect of statistical inference; additionally, AIC is the basis of a paradigm for the foundations of statistics. Akaike also made major contributions to the study of time series. As well, he had a large role in the general development of statistics in Japan.

<span class="mw-page-title-main">International Society for Bayesian Analysis</span>

The International Society for Bayesian Analysis (ISBA) is a society with the goal of promoting Bayesian analysis for solving problems in the sciences and government. It was formally incorporated as a not for profit corporation by economist Arnold Zellner and statisticians Gordon M. Kaufman and Thomas H. Leonard on 10 November 1992. It publishes the electronic journal Bayesian Analysis and organizes world meetings every other year.

Statistics models the collection, organization, analysis, interpretation, presentation of data, and is used to solve mathematical problems. Conclusions drawn from statistical analysis typically contain uncertainties, certainties or as they represent the probability of an event occurring. Statistics is fundamental to disciplines of science that involve predicting or classifying events based on a large set of data and is an integral part of fields such as machine learning, bioinformatics, genomics, and economics.

<span class="mw-page-title-main">David A. Freedman</span>

David Amiel Freedman was Professor of Statistics at the University of California, Berkeley. He was a distinguished mathematical statistician whose wide-ranging research included the analysis of martingale inequalities, Markov processes, de Finetti's theorem, consistency of Bayes estimators, sampling, the bootstrap, and procedures for testing and evaluating models. He published extensively on methods for causal inference and the behavior of standard statistical models under non-standard conditions – for example, how regression models behave when fitted to data from randomized experiments. Freedman also wrote widely on the application—and misapplication—of statistics in the social sciences, including epidemiology, public policy, and law.

<span class="mw-page-title-main">Jayanta Kumar Ghosh</span>

Jayanta Kumar Ghosh was an Indian statistician, an emeritus professor at Indian Statistical Institute and a professor of statistics at Purdue University.

<span class="mw-page-title-main">Thomas H. Leonard</span> British statistician and author (1948–2023)

Thomas Hoskyns Leonard was a British statistician. He obtained a doctorate in Statistics at the University of London and worked at the University of Warwick and the University of Wisconsin-Madison, before taking up the Chair of Statistics at the University of Edinburgh in 1995.

Kerrie Mengersen is an Australian statistician. Since 2016, she has been Distinguished Professor of Statistics at Queensland University of Technology in the Science and Engineering Faculty.

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.

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. She was president of the International Society for Bayesian Analysis (ISBA) in 2013, and chair of the Section on Bayesian Statistical Science of the American Statistical Association for 2018.

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.

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.

Christian P. Robert is a French statistician, specializing in Bayesian statistics and Monte Carlo methods.

References

  1. ↑ "Mike West The Arts & Sciences Professor of Statistics & Decision Sciences Department of Statistical Science". Duke University.
  2. ↑ "Scholars at Duke". Duke University.
  3. ↑ "Department of Statistical Science". Duke Trinity College of Arts and Sciences.
  4. 1 2 Prado, Raquel; Ferreira, Marco AR; West, Mike (2021). Time series: modeling, computation, and inference. CRC press.
  5. 1 2 West, Mike; Harrison, Jeff (1997). Bayesian Forecasting and Dynamic Models (PDF). Springer. ISBN   0-387-94725-6.
  6. 1 2 Pole, Andy; West, Mike; Harrison, Jeff (1994). Applied Bayesian Forecasting and Time Series Analysis. CRC Press. ISBN   9780367449384.
  7. ↑ Escobar, Michael; West, Mike (1995). "Bayesian density estimation and inference using mixtures" (PDF). Journal of the American Statistical Association. 90 (430): 577–588. doi:10.1080/01621459.1995.10476550.
  8. ↑ West, Mike; Blanchette, Carrie; Dressman, Holly; Huang, Erich; Ishida, Seiichi; Spang, Rainer; Zuzan, Harry; Olson Jr, John A; Marks, Jeffrey R; Nevins, Joseph R (2001). "Predicting the clinical status of human breast cancer by using gene expression profiles". Proceedings of the National Academy of Sciences. 98 (20): 11462–11467. Bibcode:2001PNAS...9811462W. doi: 10.1073/pnas.201162998 . PMC   58752 . PMID   11562467.
  9. ↑ Bild, Andrea H; Yao, Guang; Chang, Jeffrey T; Wang, Quanli; Potti, Anil; Chasse, Dawn; Joshi, Mary-Beth; Harpole, David; Lancaster, Johnathan M; Berchuck, Andrew; Olson Jr, John A; Marks, Jeffrey R; Dressman, Holly K; West, Mike; Nevins, Joseph R (2006). "Oncogenic pathway signatures in human cancers as a guide to targeted therapies". Nature. 439 (7074): 353–357. Bibcode:2006Natur.439..353B. doi:10.1038/nature04296. PMID   16273092. S2CID   4418878.
  10. ↑ "Section on Economics, Finance, and Business – Past Officers". ISBA.
  11. ↑ "Bruno de Finetti Lecture". ISBA.
  12. ↑ "Statistical Science Professor has been announced as the Bruno de Finetti Lecturer". Duke Trinity College of Arts and Sciences. 30 September 2021.
  13. ↑ "The 2nd Akaike Memorial Lecture Award". Hirotugu Akaike Memorial Website.
  14. ↑ "Mike West Receives Akaike Award". Duke Trinity College of Arts and Sciences. 2 October 2018.
  15. ↑ "Zellner Medal". ISBA.
  16. ↑ "Mitchell Prize". ISBA.
  17. ↑ "Mitchell Prize. International Society for Bayesian Analysis, & Bayesian Statistical Science Section of the American Statistical Association". Duke University.
  18. ↑ "Mike West is recipient of award from ASA NC Chapter". Duke Trinity College of Arts and Sciences. 12 October 2014.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.