Comment

作     者：Zadeh, Lotfi A. 

作者机构：Berkeley Initiative in Soft Computing (BISC) Computer Science Division and the Electronics Research Laboratory Department of EECS University of California Berkeley CA 94720 United States 

出 版 物：《Journal of the American Statistical Association》 (J. Am. Stat. Assoc.)

年 卷 期：2004年第99卷第467期

页      面：880-881页

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

基　　金：Office of Naval Research, ONR, (N00014-00-1-0621, N00014-02-1-0294) University of California Berkeley, UC Berkeley 

主　　题：REGRESSION analysis ANALYSIS of covariance SAMPLING (Statistics) DISTRIBUTION (Probability theory) BOOTSTRAPPING (Statistics) 

摘      要：Forecasting the weather presents a unique context for statistics, blending physical modeling with complicated observational data to produce information that is used at many different levels of sophistication. We are pleased that Gel, Raftery, and Gneiting (GRG) have brought this area to the attention of a statistical audience. In this discussion we give the reader a broader view of the use of ensemble techniques in numerical weather prediction (NWP). We have some comments about the use of ensembles idea presented by GRG and also present some of our recent analysis of the value of ensemble forecasts.