국내 최대 기계 및 로봇 연구정보

기술보고서

기술보고서 게시판 내용
타이틀	Goodness-of-Fit Tests for the Type-I Extreme-Value and Two-Parameter Weibull Distributions with Unknown Parameters Estimated by Graphical Plotting Techniques -Part 2:Power Study
저자	Min Liao, Toshiyuki Shimokawa
Keyword	goodness-of-fit tests; power study; Kolmogorov-Smirnov; Cramer-von Mises; Anderson-Darling; Type-I extreme-value distribution
URL	http://send.nal.go.jp/send/jpn/dlpdf.php3/naltr0001372t.pdf?id=NALTR0001372T
보고서번호	NAL TR-1372T
발행년도	1999.02
출처	NAL (National Aerospace Laboratory of Japan)
ABSTRACT	The objective of this study was to investigate the power of the Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling statistics for goodness-of-fit tests for the Type-I extreme-value and two-parameter Weibull distributions, when the population parameters were estimated by the combination of three kinds of graphical plotting techniques and the least-squares method and the maximum likelihood estimators. Monte Carlo simulation provided the power results using 10,000 repetitions for each sample size of 5, 10, 25, and 40. Four representative statistical distribution models were selected for alternative distributions in order to conduct the power comparison. The power comparisons indicated that the Anderson-Darling statistic coupled with the symmetrical ranks and the least-squares method is the most powerful statistic for goodness-of-fit tests, and is recommended for practical use.