Michael Woodroofe
Michael Barrett Woodroofe (born March 17, 1940 in Corvalis, Oregon) is an American probabilist and statistician. He is an emeritus professor of statistics and of mathematics at the University of Michigan, where he was the Leonard J. Savage Professor until his retirement. He is noted for his work in sequential analysis and nonlinear renewal theory, in central limit theory, and in nonparametric inference with shape constraints.
Michael Woodroofe | |
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Michael Woodroofe lecturing in 2002 | |
Born | Michael Barrett Woodroofe March 17, 1940 |
Nationality | American |
Alma mater | |
Scientific career | |
Fields | Statistics, Mathematics |
Institutions | University of Michigan |
Thesis | Statistical Properties of the Number of Positive Sums (1965) |
Doctoral advisor | Theodore Matthes |
Notable students | Martha Aliaga, Nancy E. Heckman, Wei Biao Wu |
Website | dept |
Education and career
Woodroofe received his Bachelor of Science from Stanford University in 1962. He went on to the University of Oregon for his masters and PhD, which he completed in 1965.
After his PhD, he spent a brief stint as an assistant professor at Carnegie Mellon University, before moving to the University of Michigan in 1968. He spent the rest of his career at Michigan, where he was a founding member of the statistic department. In 1994 he was named the Leonard J. Savage Professor, a position which he held until his retirement in 2009.[1]
Woodroofe is particularly noted for his work in sequential analysis and nonlinear renewal theory, in central limit theory, and in nonparametric inference with shape constraints.[2]
Woodroofe advised over 40 graduate students,[2][3][4] many of whom have gone on to distinguished careers of their own. He has published over 100 research articles, and 2 books. He served as editor of the Annals of Statistics from 1992 to 1994, and was the last solo editor of the journal.[2]
Awards and honors
- The Michael Woodroofe Lecture Series was established in 2008 by the University of Michigan Department of Statistics in recognition of Woodroofe's contributions.[1]
- A Conference on Nonparametric Inference and Probability with Applications to Science was held in 2005 to honor Woodroofe's career on the occasion of his 65th birthday.[5][6]
- Woodroofe is a fellow of the Institute of Mathematical Statistics.[2][7]
Selected publications
- Woodroofe, Michael; Maxwell, Michael (2000). "Central limit theorems for additive functionals of Markov chains". The Annals of Probability. 28 (2): 713–724. doi:10.1214/aop/1019160258. ISSN 0091-1798. MR 1782272.
- Woodroofe, Michael (1985). "Estimating a Distribution Function with Truncated Data". The Annals of Statistics. 13 (1): 163–177. doi:10.1214/aos/1176346584. ISSN 0090-5364. MR 0773160.
- Woodroofe, Michael (1982). Nonlinear renewal theory in sequential analysis. Philadelphia, Pa: Society for Industrial and Applied Mathematics. ISBN 0-89871-180-0. MR 0660065.
- Woodroofe, Michael (1974). Probability with applications. New York: McGraw-Hill. ISBN 0070717184. MR 0372930.
References
- "Michael Woodroofe Lecture Series". University of Michigan Statistics Department. Retrieved August 30, 2019.
- Banerjee, Moulinath; Sen, Bodhisattva (2016). "A conversation with Michael Woodroofe". Statist. Sci. 31 (3): 433–441. doi:10.1214/15-STS545. MR 3552743.
- Michael Barrett Woodroofe at the Mathematics Genealogy Project
- "Michael Woodroofe's Curriculum Vita (dated 2006)" (PDF). Michael Woodroofe's home page. Retrieved September 4, 2019.
- "More IMS Meetings Around The World" (PDF). IMS Bulletin. Vol. 34 no. 7. Institute of Mathematical Statistics. p. 22.
- Sun, Jiayang; DasGupta, Anirban; Melfi, Vince; Page, Connie, eds. (2006). Recent developments in nonparametric inference and probability. Institute of Mathematical Statistics Lecture Notes - Monograph Series. 50. Institute of Mathematical Statistics. MR 2404082. Retrieved September 28, 2019.
- "Honored IMS Fellows". Institute of Mathematical Statistics webpage. Retrieved September 28, 2019.
External links
- Michael Woodroofe publications indexed by Google Scholar