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Optimum Algorithm for Computing the Standardized Moments Using MATLAB 7.10(R2010a)
Karam Fayed
Pages - 1 - 15 | Revised - 01-05-2011 | Published - 31-05-2011
MORE INFORMATION
KEYWORDS
MATLAB Programming, Mathematics, Statistical Toolbox
ABSTRACT
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.
| 1 | Google Scholar  |
| 2 | CiteSeerX |
| 3 | refSeek |
| 4 | Scribd |
| 5 | SlideShare |
| 6 | PdfSR |
| 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. | |
| Email: karamfayed_1@hotmail.com | |
| Microsoft Corporation, “Microsoft Office professional plus, Microsoft Excel”, Version 14.0.5128.5000, 2010. | |
| Neil Salkind, “Encyclopedia of measurement and statistics”, 2007. | |
| The Mathworks, Inc., MATLAB, the Language of Technical Computing, Version 7.10.0.499 (R2010a), February 5, 2010. | |
Dr. Karam Fayed
Port Said University - Egypt
karamfayed@hotmail.com
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