Assessing the relationship of evolutionary rates and functional variables by mixture estimating equations

Autor:	Feng-Chi Chen, Pei-Sheng Lin, Shu-Fu Kuo, Yi-Hung Kung
Rok vydání:	2014
Předmět:	Statistics and Probability Mathematical optimization Binary number Asymptotic distribution Mixture distribution Probability distribution Estimating equations Statistics Probability and Uncertainty Generalized estimating equation Coding (social sciences) Mathematics
Zdroj:	Statistics & Probability Letters. 94:248-256
ISSN:	0167-7152
DOI:	10.1016/j.spl.2014.07.031
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2f0410546d0da08a4425a0dec818e13e https://doi.org/10.1016/j.spl.2014.07.031 Zobrazit plný text záznamu Full Text from ScienceDirect