A Nonparametric Way of Distribution Testing
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.
References listed on IDEAS
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- Pagan,Adrian & Ullah,Aman, 1999.
Cambridge University Press, number 9780521355643, October.
- Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521586115, October.
- Thanasis Stengos & Ximing Wu, 2010. "Information-Theoretic Distribution Test with Application to Normality," Econometric Reviews, Taylor & Francis Journals, vol. 29(3), pages 307-329.
- 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.
- Thanasis Stengos & Ximing WuÂ†, 2007. "Information-Theoretic Distribution Test with Application to Normality," Working Paper Series 24_07, The Rimini Centre for Economic Analysis.
- Thanasis Stengos & Ximing Wu, 2006. "Information-Theoretic Distribution Test with Application to Normality," Working Papers 0604, University of Guelph, Department of Economics and Finance.
- 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. Full references (including those not matched with items on IDEAS)
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