Lawrence D. Brown

Lawrence David (Larry) Brown (16 December 1940 – 21 February 2018) was Miers Busch Professor and Professor of Statistics at the Wharton School of the University of Pennsylvania in Philadelphia, Pennsylvania. He is known for his groundbreaking work in a broad range of fields including decision theory, recurrence and partial differential equations, nonparametric function estimation, minimax and adaptation theory, and the analysis of census data and call-center data.

After having been assistant professor at University of California at Berkeley, associate professor at Cornell Universitywith the latter move entailing a change from a statistics to a mathematics department, allowing him to avoid being drafted for the Vietnam War

Honors and awards

Member, American Academy of Arts and Sciences Fellow of the Institute of Mathematical Statistics (I.M.S.) Lady Davis Professorship, Hebrew University, 1988 Wilks Award of the American Statistical Association, 2002 The Provost's Award for Distinguished Ph.D. Teaching and Mentoring, University of Pennsylvania, 2011

In his honor

Institute of Mathematical Statistics Lawrence D. Brown Ph.D. Student Award

Selected publications

Books

1985. (with Olkin, I., Sacks, J., and Wynn, H.P.) Jack Carl Kiefer Collected Papers, 3 vols., Springer-Verlag, New York. 1986. (with Olkin, I., Sacks, J., and Wynn, H.P.) Jack Carl Kiefer Collected Papers Supplementary Volume, Springer-Verlag, New York. 1986. Fundamentals of Statistical Exponential Families with Applications in Statistical Decision Theory, Inst. of Math. Statist., Hayward, California. 2005. (with Plewes, T.J., and Gerstein, M.A.) Measuring Research and Development in the United States Economy, National Academies Press. 2010. (with Michael L. Cohen, Daniel L. Cork, and Constance F. Citro) Envisioning the 2020 Census. Panel on the Design of the 2020 Census Program of Evaluations and Experiments, Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC: National Academies Press.