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Testing the validity of the logistic model based on the empirical distribution function
- Source :
- Communications in Statistics - Simulation and Computation. 46:5531-5540
- Publication Year :
- 2017
- Publisher :
- Informa UK Limited, 2017.
-
Abstract
- The logistic distribution is one of the fundamental distribution and is widely used for describing model growth curves in survival analysis and biological studies. Applications of this distribution are presented in statistical literature. In this article, goodness of fit tests for the logistic distribution based on the empirical distribution function (EDF) are considered. In order to compute the test statistics, because the MLEs cannot be obtained explicitly, we use the approximate maximum likelihood estimates (AMLEs) suggested by Balakrishnan and Cohen (1990), which are simple explicit estimators. Power comparisons of the considered tests are carried out via simulations. Finally, two illustrative examples are presented and analyzed.
- Subjects :
- Statistics and Probability
Anderson–Darling test
021103 operations research
Logistic distribution
0211 other engineering and technologies
Noncentral chi-squared distribution
02 engineering and technology
Kolmogorov–Smirnov test
01 natural sciences
Distribution fitting
Empirical distribution function
010104 statistics & probability
symbols.namesake
Beta-binomial distribution
Goodness of fit
Modeling and Simulation
Statistics
symbols
0101 mathematics
Mathematics
Subjects
Details
- ISSN :
- 15324141 and 03610918
- Volume :
- 46
- Database :
- OpenAIRE
- Journal :
- Communications in Statistics - Simulation and Computation
- Accession number :
- edsair.doi...........cb71bc16717f6c9ca599556f005f3a44
- Full Text :
- https://doi.org/10.1080/03610918.2016.1165842