Modeling the Goodness-of-Fit Test Based on the Interval Estimation of the Probability Distribution Function
نویسندگان
چکیده
The paper presents a new goodness-of-fit test on the basis of the interval estimate of the probability distribution function. The comparative analysis is carried out for the proposed test and for the Kolmogorov test. The results of the numerical modeling show that the proposed test has greater performance than the Kolmogorov test in specific cases. The analysis of correlation properties of the normalized empirical cumulative distribution function is carried out. As a result, we obtain the equation for calculating the significance level of the proposed goodness-of-fit test.
منابع مشابه
A New Goodness-of-Fit Test for a Distribution by the Empirical Characteristic Function
Extended Abstract. Suppose n i.i.d. observations, X1, …, Xn, are available from the unknown distribution F(.), goodness-of-fit tests refer to tests such as H0 : F(x) = F0(x) against H1 : F(x) $neq$ F0(x). Some nonparametric tests such as the Kolmogorov--Smirnov test, the Cramer-Von Mises test, the Anderson-Darling test and the Watson test have been suggested by comparing empirical ...
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