Author, Subjects, Keywords

Cited Author

 

 
   » By Author or Editor
 » Browse Author by Alphabet
 » By Journal
 » By Subjects
 » Malaysian Journals
 » By Type
 » By Year
 » By Latest Additions
 
 
   » By Author
 » Top 20 Authors
 » Top 20 Article
 » Top Journal Cited
 » Top Article Cited
 » Journal Citation Statistics
 » Usage Since Sept 2007


 
 
 

Login | Create Account

Pengujian Kesesuaian Taburan Normal Berdasarkan Statistik Cramer-Von Mises(Test of Suitability of Normal Distribution based on Cramer-Von Mises Statistics)

Ani bin Shabri, and Abdul Aziz Jemain, (2007) Pengujian Kesesuaian Taburan Normal Berdasarkan Statistik Cramer-Von Mises(Test of Suitability of Normal Distribution based on Cramer-Von Mises Statistics). Sains Malaysiana , 36 (2). pp. 201-206. ISSN 01266039

Full text not available from this repository.

Official URL: http://pkukmweb.ukm.my/~jsm/pdf_files/SM-PDF-36-2-2007/36-2-2007-201(198kb).pdf

Affiliations

Universiti Teknologi Malaysia. Fakulti Sains. Jabatan Matematik
Universiti Kebangsaan Malaysia. Faculty of Science and Technology. Centre of Mathematical Science Studies

Abstract

Since normal distributions are the most important ones in statistics, there are large number of tests for normality. However they have less some drawbacks. Some of these tests are simple but suitable for some situations. In this study, the traditional Cramer-von Mises test statistics is modified based on Weibull formula. The new goodness-of-fit test is compared with the traditional Anderson-Darling (AD), Cramer von-Mises (CR), Kolmogorov-Smirnov (KS) and Shapiro-Wilk (SW) test statistics. A simulation study using several different distributions shows that the proposed test is very powerful for testing normality.

[Sejak taburan normal ditemui dan ianya merupakan salah satu taburan yang penting dalam statistik, terdapat banyak pengujian statistik yang dibangunkan untuk menguji kenormalan data. Namun begitu masih tidak banyak kajian yang dilakukan untuk melihat kembali keupayaan pengujian statistik yang sedia ada. Sebahagian daripada pengujian statistik didapati mudah tetapi hanya sesuai untuk sesuatu keadaan. Dalam kajian ini, pengujian statistik berdasarkan statistik Cramer-von Mises cuba diperbaiki berdasarkan rumus Weibull. Kekuatan statistik yang baru ini dibandingkan kekuatan dengan statistik traditional Anderson-Darling (AD), Cramer von-Mises (CR), Kolmogorov-Smirnov (KS) dan Shapiro-Wilk (SW). Kajian simulasi berdasarkan beberapa taburan yang berbeza menunjukkan pengujian statistik yang dicadangkan paling sesuai untuk menguji kenormalan].

Item Type:Journal
Keywords:Test of normality; Cramer von-Mises; Kolmogorov-Smirnov; Shapiro-Wilk
Subjects:Q Science, Computer Science
ID Code:2839

Chowdhury, J.U., Stedinger, J.R. & Lu, L. 1991. Goodness-of-Fit Tests for Regional Generalized Extreme Value Flood Distributions, Water Resources Research 27(7): 1765-1776.

Cohen, A.C. & Whitten, B.J. 1988. Parameter Estimation in Realiability and Life Span Models. Marcel Dekker, Inc. New York.

D’Agostino, R.B. & Stephens, M.A. 1986. Goodness-of-fit Techniques. New York: Dekker.

Maidment, D.R. 1992. Handbook of Hydrology. McGraw-Hill, Inc.

Pavur, R.J., Edgeman, R.L. & Scott, R.C. 1992. Quadratic Statistics for the Goodness-of-Fit Test of the Inverse Gaussian Distribution, IEEE Transactions on Reliability 41: 118-123.

Rao, A.R. & Hamed, K.H., 2000. Flood Frequency Analysis, CMC Press LLC, New York.

Swanepoel, J.W.H. & Graan, F.C.V. 2002. Goodness-of-fit Tests Based On Estimated Expectations of Probability Integral Transformed Order Statistics. Annals of the Institute of Statistical Mathematics 54(3): 531-542.

Zhang, J. & Wu, Y. 2005. Likelihood-Ratio Tests for Normality. Computational Statistics & Data Analysis 49: 709-721.

Repository Staff Only: item control page