A New Goodness-of-Fit Test for a Distribution by the Empirical Characteristic Function
نویسندگان
چکیده مقاله:
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 distribution, Fn(x), and the known distribution F0(x). The characteristic function is important in characterizing the probability distribution theoretically. Thus it have been expected that the empirical characteristic function, cn(t), can be used for suggesting a goodness-of-fit test...[To Continue click here]
منابع مشابه
A Goodness-of-fit Test for the Distribution Tail
In order to check that a parametric model provides acceptable tail approximations, we present a test which compares the parametric estimate of an extreme upper quantile with its semiparametric estimate obtained by extreme value theory. To build this test, the sampling variations of these estimates are approximated through parametric bootstrap. Numerical Monte Carlo simulations explore the cover...
متن کاملEMPIRICAL CHARACTERISTIC FUNCTION APPROACH TO GOODNESS-OF-FIT TESTS FOR THE CAUCHY DISTRIBUTION WITH PARAMETERS ESTIMATED BY MLE OR ElSE
We consider goodness-of-fit tests of the Cauchy distribution based on weighted integrals of the squared distance between the empirical characteristic function of the standardized data and the characteristic function of the standard Cauchy distribution. For standardization of data Ciirtler and Henze (2000, Annals of the Institute of Statistical Mathematics, 52, 267-286) used the median and the i...
متن کاملEmpirical Characteristic Function Approach to Goodness-of-Fit Tests for the Cauchy Distribution with Parameters Estimated by MLE or EISE
We consider goodness-of-fit tests of Cauchy distribution based on weighted integrals of the squared distance of the difference between the empirical characteristic function of the standardized data and the characteristic function of the standard Cauchy distribution. For standardization of data Gürtler and Henze (2000) used the median and the interquartile range. In this paper we use maximum lik...
متن کاملA Goodness of Fit Test For Exponentiality Based on Lin-Wong Information
In this paper, we introduce a goodness of fit test for expo- nentiality based on Lin-Wong divergence measure. In order to estimate the divergence, we use a method similar to Vasicek’s method for estimat- ing the Shannon entropy. The critical values and the powers of the test are computed by Monte Carlo simulation. It is shown that the proposed test are competitive with other tests of exponentia...
متن کاملEmpirical Characteristic Function Approach to Goodness of Fit Tests for the Logistic Distribution under SRS and RSS
متن کامل
Goodness-of-Fit Tests for Symmetric Stable Distributions – Empirical Characteristic Function Approach
We consider goodness-of-fit tests of symmetric stable distributions based on weighted integrals of the squared distance between the empirical characteristic function of the standardized data and the characteristic function of the standard symmetric stable distribution with the characteristic exponent α estimated from the data. We treat α as an unknown parameter, but for theoretical simplicity w...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 2 شماره 1
صفحات 1- 13
تاریخ انتشار 2005-09
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023