Arthur P. Dempster
| Arthur P. Dempster | |
|---|---|
 Prof Dempster at the workshop on Belief Function Theory (Brest 1 April 2010). | |
| Born | 1929 (age 86–87) |
| Fields | Statistics |
| Institutions | Harvard University |
| Alma mater |
Princeton University (PhD 1956) University of Toronto (BA 1952; MA 1953) |
| Thesis | The two-sample multivariate problem in the degenerate case (1956) |
| Doctoral advisor | John Tukey |
| Doctoral students | Nan Laird |
| Known for |
Dempster–Shafer theory, EM algorithm |
| Notable awards |
Putnam Fellow (1961) ASA Fellow (1964) [1] IMS Fellow (1963) [2] Guggenheim Fellow AAAS Fellow (1997) |
Arthur Pentland Dempster (born 1929) is a Professor Emeritus in the Harvard University Department of Statistics. He was one of four faculty when the department was founded in 1957.[3]
Biography
Dempster received his B.A. in mathematics and physics (1952) and M.A. in mathematics (1953), both from University of Toronto. He obtained his Ph.D. in mathematical statistics from Princeton University in 1956. His thesis, titled The two-sample multivariate problem in the degenerate case, was written under the supervision of John Tukey.
Academic works
Among his contributions to statistics are the Dempster–Shafer theory and the expectation-maximization (EM) algorithm.
Selected publications
- Dempster, A. P. (1967), "Upper and lower probabilities induced by a multivalued mapping", The Annals of Mathematical Statistics, 38 (2): 325–339, doi:10.1214/aoms/1177698950
- Dempster, A. P.; Laird, N.; Rubin, D. B. (1977), "Maximum likelihood from incomplete data via the EM algorithm", Journal of the Royal Statistical Society, Series B, 39 (1): 1–38, JSTOR 2984875
Honors and awards
Dempster was a Putnam Fellow in 1951. He was elected to ASA Fellow in 1964,[1] IMS Fellow in 1963,[2] and AAAS Fellow in 1997.
References
- 1 2 "Search Fellows of the ASA". amstat.org. ASA. Retrieved 3 February 2015.
click submit and search "Dempster"
- 1 2 Honored IMS Fellows
- ↑ Date information sourced from Library of Congress Authorities data, via corresponding WorldCat Identities linked authority file (LAF) .