More powerful goodness-of-fit tests for uniform stochastic ordering

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Comparison Between Goodness of Fit Tests for Copula

‎Copula functions as a model can show the relationship between variables‎. ‎Appropriate copula function for a specific application is a function that shows the dependency between data in a best way‎. ‎Goodness of fit tests theoretically are the best way in selection of copula function‎. ‎Different ways of goodness of fit for copula exist‎. ‎In this paper we will examine the goodness of fit test...

متن کامل

Powerful goodness-of-fit tests based on the likelihood ratio

A new approach of parameterization is proposed to construct a general goodnessof-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér– von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

متن کامل

Goodness of Fit Tests in Stochastic Frontier Models

In this paper we discuss goodness of fit tests for the distribution of technical inefficiency in stochastic frontier models. If we maintain the hypothesis that the assumed normal distribution for statistical noise is correct, the assumed distribution for technical inefficiency is testable. We show that a goodness of fit test can be based on the distribution of estimated technical efficiency, or...

متن کامل

Goodness-of-Fit for Revealed Preference Tests

I describe a goodness-of-fit measure for revealed preference tests. This index can be used to measure the degree to which an economic agent violates the model of utility maximization. I calculate the violation indices for a 38 consumers and find that the observed choice behavior is very close to optimizing behavior.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Computational Statistics & Data Analysis

سال: 2020

ISSN: 0167-9473

DOI: 10.1016/j.csda.2019.106898