الفهرس 
Title : Goodness of fit tests using the natural statistical transforms
AbstractOnly 14 pages are availabe for public view
 |  | from | 95 |  |  |
| | | from | 95 | | |
Abstract
In this thesis, a new goodness of fit test for the Beta distribution that employs the empirical Laplace transform is presented.The proposed test is formed using Kummer{u2019}s differential equation, and its Laplace transform as indication of the validity of Beta distribution. The difference between the two sides of the equation is taken as measure of the deviation of the empirical data and the Beta distribution.The consistency of the test statistical and its asymptotic distribution under the null hypothesis are investigated theoretically and empirically. The decay of the test weight function tends to infinity, and the test statistics approach limit values related to the first non-zero component of Neyman{u2019}s smooth test for the Beta distribution. For practical investigation of this test, a simulation study is conducted to compare the new test with other well-known tests for the Beta distribution. The significance of this thesis is derived from the scarcity of statistical inference procedures in the literature