نتایج جستجو برای: Cramer-Von-Mises
تعداد نتایج: 99289 فیلتر نتایج به سال:
This paper introduces speci"cation tests of parametric mean-regression models. The null hypothesis of interest is that the parametric regression function is correctly speci"ed. The proposed tests are generalizations of the Kolmogorov}Smirnov and Cramer}von Mises tests to the regression framework. They are consistent against all alternatives to the null hypothesis, powerful against 1/Jn local al...
A Data Driven Parameter Estimation for the Three- Parameter Weibull Population from Censored Samples
A method is described for the calculation of the three-parameter Weibull distribution function from censored samples. The method introduces a data driven technique based on an adapted Gaussian like kernel to match the censoring scheme. The method minimizes the Cramer von Mises distance from a non-parametric density estimate and the parametric estimate at the order statistics. The maximum likeli...
This paper considers partially linear varying coefficient models when the response variable is missing at random. The paper uses imputation techniques to develop an omnibus specification test. The test is based on a simple modification of a Cramer von Mises functional that overcomes the curse of dimensionality often associated with the standard Cramer von Mises functional. The paper also consid...
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 ...
This article presents a derivation of the distribution of the Kolmogorov–Smirnov, Cramer–von Mises, and Anderson–Darling test statistics in the case of exponential sampling when the parameters are unknown and estimated from sample data for small sample sizes via maximum likelihood.
Abstract In low count-rate experiments Gaussian statistics is often not appropriate. An example of likelihood analysis applied to determine the Kr activity using data from a low background liquid scintillator is presented. Uncertainties and upper limits calculation is shown together with a goodness-of-fit based on Monte Carlo and on the Smirnov-Cramer-Von Mises test. The likelihood ratio method...
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