Assessing the relationship of evolutionary rates and functional variables by mixture estimating equations |
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| Institution: | 1. Division of Biostatistics and Bioinformatics, National Health Research Institutes, Taiwan;2. Department of Mathematics, National Chung Cheng University, Taiwan;3. Department of Dentistry, China Medical University, Taiwan;1. Department of Mathematics, Jinan University, Guangzhou, 510630, PR China;2. Department of Applied Mathematics, Pai Chai University, Taejon, 302-735, South Korea;1. Mathematical Sciences Center and Tsinghua Center for Statistics Science, Tsinghua University, Beijing 100084, China;2. School of Economics and Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, Xiamen 361005, China;3. School of Business, Renmin University of China, Beijing 100084, China;1. Afdeling Statistiek, Celestijnenlaan 200b - bus 2400, 3001 Leuven, Belgium;2. Faculty of Business and Economics, ORSTAT, KU Leuven, Belgium;1. Kazakh-British Technical University, Almaty 050000, Kazakhstan;2. School of Mathematics, University of Manchester, Manchester M13 9PL, UK;3. Applied Mathematics Group, Industrial Research Limited, Lower Hutt, New Zealand;4. Kazakh National University, Almaty, Kazakhstan |
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| Abstract: | In the study of complex organisms, clarifying the association between the evolution of coding genes and the measures of functional variables is of fundamental importance. However, traditional analysis of the evolutionary rate is either built on the assumption of independence between responses or fails to handle a mixture distribution problem. In this paper, we utilize the concept of generalized estimating equations to propose an estimating equation to accommodate continuous and binary probability distributions. The proposed estimate can be shown to have consistency and asymptotic normality. Simulations and data analysis are also presented to illustrate the proposed method. |
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| Keywords: | Evolutionary rate Generalized estimating equation Mixture distribution |
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