Texas A&M University
Department of Statistics
invites Nominations for
The Emanuel and Carol Parzen
Prize for Statistical Innovation
Department
of Statistics
Texas A&M University
To promote the dissemination of statistical achievements, the Emanuel and Carol
Parzen Prize for Statistical Innovation is awarded (around April of even
numbered years) to North American statisticians who have made outstanding and
influential contributions to the development of applicable and innovative
statistical methods. The Parzen prize is awarded by the Department of
Statistics at Texas A&M University to a nominee selected by the members of
the Parzen Prize Committee who for 2006 are: Suojin Wang, James Matis, Bradley
Efron, Grace Wahba, and William Schucany.
Nominations for the 2006 Parzen Prize should be submitted by November 1,
2005 to:
Professor Suojin Wang
Department of Statistics
3143 TAMU
Texas A&M University
College Station, TX 77843-3143
Previous Parzen Prize winners, and
their Parzen Prize lectures are:
1994 - Grace
Wahba, Bascom Professor of Statistics at the University of Wisconsin:
lecture entitled “Statistical Models, Reproducing Kernels, Machine Learning,
Multivariate Function Estimation, Cross Validation and all that . . .”
1996 - Donald
P. Rubin, Professor of Statistics at Harvard University; lecture entitled “Merging
Statistical and Econometric Approaches to Causal Inference in Nonrandomized
Studies.”
1998 - Bradley
Efron, Professor of Statistics and Max H. Stein Professor of Humanities and
Sciences, Stanford University); lecture entitled “Astrophysics and
Biostatistics: An Odd Couple.”
2000 - C.R.
Rao, Eberly Professor of Statistics and Director of the Center for
Multivariate Analysis at Pennsylvania State University; “Statistics: A
Technology for the Millenium.”
2002 - David
R. Brillinger, Professor of Statistics, University of California, Berkeley; “Mutual Information: A Unifying Concept of Random Process Analysis.”
2004 - Jerome
H. Friedman, Department of Statistics, Stanford University’ “Gradient
Directed Regularization for Linear Regression and Classification.”
Emanuel Parzen is Distinguished Professor of Statistics at Texas A&M University. In 1994 he was awarded the Samuel S. Wilks Memorial Medal of the American Statistical Association “for outstanding research in Time Series Analysis, especially for his innovative introduction of reproducing kernel spaces, spectral analysis and spectrum smoothing; for pioneering contributions in quantile and density quantile functions and estimation; for unusually successful and influential textbooks in Probability and Stochastic Processes; for excellent and enthusiastic teaching and dissemination of statistical knowledge; and for a commitment to service on Society Councils, Government Advisory Committees, and Editorial Boards.”
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