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Bayesian Subset Selection for Reproductive Dispersion Linear Models

Author

Listed:
  • Zhao Yuanying

    (College of Mathematics and Information Science, Guiyang University, Guiyang, 550005, China)

  • Xu Dengke

    (Department of Statistics, Zhejiang Agriculture and Forest University, Lin’an, 311300, China)

  • Duan Xingde

    (Department of Mathematics, Chuxiong Normal College, Chuxiong, 675000, China)

  • Pang Yicheng

    (School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang, 550025, China)

Abstract

We propose a full Bayesian subset selection method for reproductive dispersion linear models, which bases on expanding the usual link function to a function that incorporates all possible subsets of predictors by adding indictors as parameters. The vector of indicator variables dictates which predictors to delete. An efficient MCMC procedure that combining Gibbs sampler and Metropolis-Hastings algorithm is presented to approximate the posterior distribution of the indicator variables. The promising subsets of predictors can be identified as those with higher posterior probability. Several numerical examples are used to illustrate the newly developed methodology.

Suggested Citation

  • Zhao Yuanying & Xu Dengke & Duan Xingde & Pang Yicheng, 2014. "Bayesian Subset Selection for Reproductive Dispersion Linear Models," Journal of Systems Science and Information, De Gruyter, vol. 2(1), pages 77-85, February.
  • Handle: RePEc:bpj:jossai:v:2:y:2014:i:1:p:77-85:n:7
    DOI: 10.1515/JSSI-2014-0077
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    References listed on IDEAS

    as
    1. Fu, Ying-Zi & Tang, Nian-Sheng & Chen, Xing, 2009. "Local influence analysis of nonlinear structural equation models with nonignorable missing outcomes from reproductive dispersion models," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3671-3684, August.
    2. Tang, Nian-Sheng & Wei, Bo-Cheng & Wang, Xue-Ren, 2000. "Influence diagnostics in nonlinear reproductive dispersion models," Statistics & Probability Letters, Elsevier, vol. 46(1), pages 59-68, January.
    3. Chen, Xue-Dong & Tang, Nian-Sheng, 2010. "Bayesian analysis of semiparametric reproductive dispersion mixed-effects models," Computational Statistics & Data Analysis, Elsevier, vol. 54(9), pages 2145-2158, September.
    4. Tang, Nian-Sheng & Zhao, Yuan-Ying, 2013. "Semiparametric Bayesian analysis of nonlinear reproductive dispersion mixed models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 68-83.
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