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http://dx.doi.org/10.7465/jkdi.2012.23.1.089

Likelihood based inference for the ratio of parameters in two Maxwell distributions  

Kang, Sang-Gil (Department of Computer and Data Information, Sangji University)
Lee, Jeong-Hee (School of Public Health, Daegu Haany University)
Lee, Woo-Dong (Department of Asset Management, Daegu Haany University)
Publication Information
Journal of the Korean Data and Information Science Society / v.23, no.1, 2012 , pp. 89-98 More about this Journal
Abstract
In this paper, the ratio of parameters in two independent Maxwell distributions is parameter of interest. We proposed test statistics, which converge to standard normal distribution, based on likelihood function. The exact distribution for testing the ratio is hard to obtain. We proposed the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic for testing the ratio. Through simulation, we show that the modified signed log-likelihood ratio statistic converges faster than signed log-likelihood ratio statistic to standard normal distribution. We compare two statistics in terms of type I error and power. We give an example using real data.
Keywords
Maximum likelihood estimate; modified signed log-likelihood statistic; signed log-likelihood statistic; standard normal distribution;
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