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

Author

Listed:
  • Lin, Pei-Sheng
  • Chen, Feng-Chi
  • Kuo, Shu-Fu
  • Kung, Yi-Hung

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.

Suggested Citation

  • Lin, Pei-Sheng & Chen, Feng-Chi & Kuo, Shu-Fu & Kung, Yi-Hung, 2014. "Assessing the relationship of evolutionary rates and functional variables by mixture estimating equations," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 248-256.
    • Handle: RePEc:eee:stapro:v:94:y:2014:i:c:p:248-256
    DOI: 10.1016/j.spl.2014.07.031
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    References listed on IDEAS

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    1. Pei-Sheng Lin, 2008. "Estimating equations for spatially correlated data in multi-dimensional space," Biometrika, Biometrika Trust, vol. 95(4), pages 847-858.
    2. Wei Pan, 2001. "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 57(1), pages 120-125, March.
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