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| Optimum Algorithm for Computing the Standardized Moments Using MATLAB 7.10(R2010a)
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Full
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 PDF(563.1KB) |
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Source |
International Journal of Scientific and Statistical Computing (IJSSC) |
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Table of Contents |
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Download
Complete Issue PDF(1.01MB) |
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Volume: 2 Issue: 1 |
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Pages: NULL |
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Publication
Date: July / August 2011 |
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ISSN
(Online): 2180-1339 |
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Pages |
1 - 15 |
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Author(s) |
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Published
Date |
31-05-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: MATLAB Programming, Mathematics, Statistical Toolbox |
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| This Manuscript is indexed in the following databases/websites:- |
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| 1. Scribd |
| 2. Google Scholar |
| 3. Docstoc |
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| A fundamental task in many statistical analyses is to characterize the location and variability of a data set. A further characterization of the data includes skewness and kurtosis. This paper emphasizes the real time computational problem for generally the rth standardized moments and specially for both skewness and kurtosis. It has therefore been important to derive an optimum computational technique for the standardized moments. A new algorithm has been designed for the evaluation of the standardized moments. The evaluation of error analysis has been discussed. The new algorithm saved computational energy by approximately 99.95% than that of the previously published algorithms. |
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| 1 |
Neil Salkind, “Encyclopedia of measurement and statistics”, 2007.
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| 2 |
D.N.Joanes&C.A.Gill,”Comparing measures of sample skewness and kurtosis”, Journal of the royal statistical society (series D), Vol.47, No.1,page 183-189, March,1998.
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Microsoft Corporation, “Microsoft Office professional plus, Microsoft Excel”, Version 14.0.5128.5000, 2010.
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The Mathworks, Inc., MATLAB, the Language of Technical Computing, Version 7.10.0.499 (R2010a), February 5, 2010.
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Email: karamfayed_1@hotmail.com
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| Karam Fayed : Colleagues
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