A new moment matching algorithm for sampling from partially specified symmetric distributions

作     者：Date, P. Mamon, R. Jalen, L. 

作者机构：Brunel Univ Dept Math Sci Ctr Anal Risk & Optimizat Modelling Appl Uxbridge UB8 3PH Middx England Univ Western Ontario Dept Stat & Actuarial Sci London ON N6A 3K7 Canada 

出 版 物：《OPERATIONS RESEARCH LETTERS》 (运筹学快报)

年 卷 期：2008年第36卷第6期

页      面：669-672页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：Royal Society 

主　　题：Scenario generation Semidefinite programming 

摘      要：A new algorithm is proposed for generating scenarios from a partially specified symmetric multivariate distribution. The algorithm generates samples which match the first two moments exactly, and match the marginal fourth moments approximately, using a semidefinite programming procedure. The performance of the algorithm is illustrated by a numerical example. (C) 2008 Elsevier B.V. All rights reserved.