:: Volume 9, Issue 2 (3-2013) ::
JSRI 2013, 9(2): 115-131 Back to browse issues page
A Cumulative Residual Entropy Characterization of the Rayleigh Distribution and Related Goodness-of-Fit Test
S. Baratpour 1, F. Khodadadi
1- , baratpour@um.ac.ir
Abstract:   (4155 Views)

Rayleigh distribution is widely used for life-time modeling and is important in electro vacuum devices and communication engineering. Rao et al. (2004) suggested the Cumulative Residual Entropy (CRE), which is the extension of the Shannon entropy to the the cumulative distribution function. In this paper, a general class of maximum CRE distributions is introduced and then we characterize the Rayleigh distribution and use it to construct a goodness-of-fit test for ascertaining appropriateness of such model. For constructing the test statistics, we use Cumulative residual Kullback-Leibler information (CKL) that was introduced by Baratpour and Habibi (2012). Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for the test statistics. A Monte Carlo power analysis is performed for various alternatives and sample sizes in order to compare the proposed test with several existing goodness-of-fit tests based on the empirical distribution. We find that the proposed test has good power properties. The use of the proposed test is shown in an illustrative example.

Keywords: Cumulative residual entropy, maximum entropy, Kullback-Leibler divergence, Rayleigh distribution, goodness of fit, power study
Full-Text [PDF 202 kb]   (3194 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/08/16 | Accepted: 2016/08/16 | Published: 2016/08/16

XML   Persian Abstract   Print

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 9, Issue 2 (3-2013) Back to browse issues page