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Variable Selection in Regression Mixture Modeling for the Discovery of Gene Regulatory Networks

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  • Gupta, Mayetri
  • Ibrahim, Joseph G.

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  • Gupta, Mayetri & Ibrahim, Joseph G., 2007. "Variable Selection in Regression Mixture Modeling for the Discovery of Gene Regulatory Networks," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 867-880, September.
    • Handle: RePEc:bes:jnlasa:v:102:y:2007:m:september:p:867-880
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    Citations

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    Cited by:

    1. Aijun Yang & Xuejun Jiang & Lianjie Shu & Jinguan Lin, 2017. "Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis," Computational Statistics, Springer, vol. 32(1), pages 127-143, March.
    2. Posch, Konstantin & Arbeiter, Maximilian & Pilz, Juergen, 2020. "A novel Bayesian approach for variable selection in linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    3. Alhamzawi, Rahim, 2016. "Bayesian model selection in ordinal quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 68-78.
    4. Gregor Zens, 2019. "Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 1019-1051, December.
    5. Lee, Kuo-Jung & Feldkircher, Martin & Chen, Yi-Chi, 2021. "Variable selection in finite mixture of regression models with an unknown number of components," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    6. Aijun Yang & Yunxian Li & Niansheng Tang & Jinguan Lin, 2015. "Bayesian variable selection in multinomial probit model for classifying high-dimensional data," Computational Statistics, Springer, vol. 30(2), pages 399-418, June.
    7. Jian Zhang, 2017. "Screening and clustering of sparse regressions with finite non-Gaussian mixtures," Biometrics, The International Biometric Society, vol. 73(2), pages 540-550, June.
    8. Lee, Kuo-Jung & Chen, Ray-Bing & Wu, Ying Nian, 2016. "Bayesian variable selection for finite mixture model of linear regressions," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 1-16.
    9. Moser Carlee & Gupta Mayetri, 2012. "A Generalized Hidden Markov Model for Determining Sequence-based Predictors of Nucleosome Positioning," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(2), pages 1-23, January.
    10. Baragatti, M. & Pommeret, D., 2012. "A study of variable selection using g-prior distribution with ridge parameter," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1920-1934.

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