A Nonparametric Way of Distribution Testing

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A Nonparametric Way of Distribution Testing

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Ekrem Kilic (Istanbul Bilgi University)

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Ekrem Kilic

Abstract

Testing the distribution of a random sample can be considered ,indeed, as a goodness-of-fit problem. If we use the nonparametric density estimation of the sample as a consistent estimate of exact distribution, the problem reduces, more specifically, to the distance of two functions. This paper examines the distribution testing from this point of view and suggests a nonparametric procedure. Although the procedure is applicable for all distributions, paper emphasizes on normality test.The critical values for this normality test generated by using Monte Carlo techniques.

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Paper provided by EconWPA in its series Econometrics with number 0510006.

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Length: 22 pages
Date of creation: 29 Oct 2005
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Handle: RePEc:wpa:wuwpem:0510006

Note: Type of Document - pdf; pages: 22
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Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

This paper has been announced in the following NEP Reports:

NEP-ALL-2005-11-05 (All new papers)
NEP-ECM-2005-11-05 (Econometrics)

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

Thanasis Stengos & Ximing Wu, 2006. "Information-Theoretic Distribution Test with Application to Normality," Working Papers 0604, University of Guelph, Department of Economics. [Downloadable!]
Other versions:
- Thanasis Stengos & Ximing Wu, 2006. "Information-Theoretic Distribution Test with Application to Normality," University of Cyprus Working Papers in Economics 3-2006, University of Cyprus Department of Economics. [Downloadable!]
Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259. [Downloadable!] (restricted)

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