DISTRIBUTION AND MOMENTS OF THE WEIGHTED SUM OF UNIFORM RANDOM-VARIABLES, WITH APPLICATIONS IN REDUCING MONTE-CARLO SIMULATIONS

被引：36

作者：

KAMGARPARSI, B

BROSH, M

机构：

[1] USN,RES LAB,NAVY CTR APPL RES ARTIFICIAL INTELLIGENCE,WASHINGTON,DC 20375

[2] UNIV MARYLAND,CTR AUTOMAT RES,COLLEGE PK,MD 20742

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 1995年 / 52卷 / 04期

关键词：

CENTRAL LIMIT; DIGITIZATION ERROR; MONTE CARLO SIMULATION; SUM OF RANDOM VARIABLES; UNIFORM DISTRIBUTION;

D O I：

10.1080/00949659508811688

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We derive analytical expressions for the distribution function and the moments of the weighted sum Y = Sigma(i=1)(N) a(i)X(i), where X(i) are independent random variables with non-identical uniform distributions, for an arbitrary number of variables N, and arbitrary coefficient values a(i). These results are the generalizations of those for the regular sum of uniform random variables. Using the results, we examine the inadequacy of the central limit approximation for finite N. We also discuss the savings in the cost of computing properties of the weighted sum using these results vs. Monte Carlo simulations. We give an example of the application of the weighted sum to analyzing the effects of digitization error in computer vision.

引用

页码：399 / 414

页数：16

共 15 条

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