2008/02/01 by Grace L. Yang · 1 citation
Mathematics · #Survey Sampling and Estimation Techniques #stat.ME
paper · pdf · doi:10.1214/07-sts246a
published as Statistical Science 2008, Vol. 23, No. 1, 69-75 · Published in at http://dx.doi.org/10.1214/07-STS246A the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
openalex publication_date 2008/02/01 · arxiv created 2008/08/05 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
martingales, effect of radiation, shoulder effect, competing risks. Professor Brillinger wrote a very stimulating paper on Neyman’s life history and some of his contributions to applied statistics. The paper’s central theme is to review how Neyman used stochastic processes in data analysis. The paper contains a number of illuminating examples of Neyman and of Brillinger with other collaborators. I am honored to have been invited to be a discussant. Professor Brillinger quoted Neyman (1960), “The time has arrived for the theory of stochastic processes to become an item of usual equipment of every applied statistician. ” In the post-Neyman era, data come in our way fast and in all forms, such as streams, functions, manifolds, random shapes, trees and images. The importance of the theory of stochastic processes in applied statistics cannot be overemphasized. Brillinger’s observation of Neyman’s thought processes in conducting applied research resonates with me. My discussion will be primarily to amplify it from a somewhat different perspective, namely from Neyman’s teaching and his research projects on sampling and cancer. Included in the discussion will be recalls of some of my personal experience having Neyman as a teacher. Neyman’s sampling and cancer projects are selected in this discussion in part because of their broad impact which appears to be not a focus of Brillinger’s paper. Although Neyman’s