There are some existing commonly used goodness-of-fit tests, such as the Kolmogorov-Smirnov test, the Cramer-Von Mises test, and the Anderson-Darling test. In addition, a new goodness-of-fit test named G test was proposed by Chen and Ye (2009). The purpose of this thesis is to compare the performance of some goodness-of-fit tests by comparing their power.
A goodness-of-fit test is usually used when judging whether or not the underlying population distribution differs from a specific distribution. This research focus on testing whether the underlying population distribution is an exponential distribution.
To conduct statistical simulation, SAS/IML is used in this research. Some alternative distributions such as the triangle distribution, V-shaped triangle distribution are used. By applying Monte Carlo simulation, it can be concluded that the performance of the Kolmogorov-Smirnov test is better than the G test in many cases, while the G test performs well in some cases.
| Identifer | oai:union.ndltd.org:fiu.edu/oai:digitalcommons.fiu.edu:etd-3783 |
| Date | 06 July 2016 |
| Creators | Liu, Tianyi |
| Publisher | FIU Digital Commons |
| Source Sets | Florida International University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | FIU Electronic Theses and Dissertations |
Page generated in 0.0095 seconds