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A Penalized Likelihood Approach for Bivariate Conditional Normal Models for Dynamic Co-expression Analysis

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  • Jun Chen
  • Jichun Xie
  • Hongzhe Li

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  • Jun Chen & Jichun Xie & Hongzhe Li, 2011. "A Penalized Likelihood Approach for Bivariate Conditional Normal Models for Dynamic Co-expression Analysis," Biometrics, The International Biometric Society, vol. 67(1), pages 299-308, March.
    • Handle: RePEc:bla:biomet:v:67:y:2011:i:1:p:299-308
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01413.x
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    References listed on IDEAS

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    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
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    Cited by:

    1. Zichen Ma & Shannon W. Davis & Yen‐Yi Ho, 2023. "Flexible copula model for integrating correlated multi‐omics data from single‐cell experiments," Biometrics, The International Biometric Society, vol. 79(2), pages 1559-1572, June.
    2. Tianwei Yu, 2018. "A new dynamic correlation algorithm reveals novel functional aspects in single cell and bulk RNA-seq data," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-22, August.

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