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Goodness-of-fit test for exponentiality based on spacings for general progressive Type-II censored data.
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- Author(s): Qin, Xinyan1 (AUTHOR); Yu, Jiao1 (AUTHOR); Gui, Wenhao1 (AUTHOR)
- Source:
Journal of Applied Statistics. Mar 2022, Vol. 49 Issue 3, p599-620. 22p. 2 Diagrams, 13 Charts, 3 Graphs.- Subject Terms:
- Source:
- Additional Information
- Abstract: There have been numerous tests proposed to determine whether or not the exponential model is suitable for a given data set. In this article, we propose a new test statistic based on spacings to test whether the general progressive Type-II censored samples are from exponential distribution. The null distribution of the test statistic is discussed and it could be approximated by the standard normal distribution. Meanwhile, we propose an approximate method for calculating the expectation and variance of samples under null hypothesis and corresponding power function is also given. Then, a simulation study is conducted. We calculate the approximation of the power based on normality and compare the results with those obtained by Monte Carlo simulation under different alternatives with distinct types of hazard function. Results of simulation study disclose that the power properties of this statistic by using Monte Carlo simulation are better for the alternatives with monotone increasing hazard function, and otherwise, normal approximation simulation results are relatively better. Finally, two illustrative examples are presented. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Journal of Applied Statistics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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