Using one-parameter sub-family of distributions in empirical likelihood ratio with censored data |
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| Institution: | 166121. Department of Statistics, University of Kentucky, Lexington, KY 40506-0027, USA;1. Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia;2. Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt;3. Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan;4. Department of Mathematics, Faculty of Science Helwan University, Cairo, Egypt;5. Mathematics (Statistics Option) program, Pan African University, Institute for Basic Science, Technology and Innovation (PAUSTI), Nairobi 6200-00200, Kenya;1. Faculty of Medicine, University of Ottawa;2. Epidemiology and Community Medicine, University of Ottawa;3. Ottawa Hospital Research Institute;4. ICES uOttawa;5. Medicine, University of Alberta, 8440 112 St NW, Edmonton, AB T6G 2P4, Canada;6. Alberta Innovates—Health Solutions;1. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, 510000, China;2. Key Laboratory of Machine Intelligence and Advanced Computing(Sun Yat-sen University), Ministry of Education, China;1. School of Transportation, Southeast University, Nanjing, China;2. School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, China |
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| Abstract: | Recently, it has been shown that empirical likelihood ratios can be used to form confidence intervals and test hypothesis just like the parametric case. We illustrate here the use of a particular kind of one-parameter sub-family of distributions in the analysis of empirical likelihood with censored data. This approach not only simplifies the theoretical analysis of the limiting behavior of the empirical likelihood ratio, it also gave us clues for the numerical search of constrained maxima of an empirical likelihood. |
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