Modified goodness-of-fit tests for the logistic distribution with unknown location and scale parameters
Titel:
Modified goodness-of-fit tests for the logistic distribution with unknown location and scale parameters
Auteur:
Woodruff, Brian W. Yoder, John D. Moore, Albert H. Dunne, Edward J.
Verschenen in:
Communications in statistics
Paginering:
Jaargang 15 (1986) nr. 1 pagina's 77-83
Jaar:
1986
Inhoud:
The standard Kolmogorov-Smirnov, Anderson-Darling, and Cramer-bon Mises tests require continuous underlying distributions with known parameters. When the parameters are not known, but must be estimated from the sample data, the standard tables are no longer valid. This paper gives tables of critical values for the logistic distribution with unknown location and scale parameters. The powers of these tests are given for a number of alternative distributions. The results of the power study indicate that the modified tests do well at distinguishing between a logistic distribution and a distribution that has a very different shape. However, the powers are not very good when trying to distinguish between the logistic and a similar-shaped distribution, such as the normal.