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Consistent linear model selection

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  • Zhao, Meng
  • Kulasekera, K.B.

Abstract

In this note we derive the rate of divergence of the penalty term for consistent model selection in the linear regression model under a general error structure.

Suggested Citation

  • Zhao, Meng & Kulasekera, K.B., 2006. "Consistent linear model selection," Statistics & Probability Letters, Elsevier, vol. 76(5), pages 520-530, March.
    • Handle: RePEc:eee:stapro:v:76:y:2006:i:5:p:520-530
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    References listed on IDEAS

    as
    1. Peide Shi & Chih‐Ling Tsai, 2002. "Regression model selection—a residual likelihood approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 237-252, May.
    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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    6. Xingcai Zhou & Hao Shen, 2022. "Communication-Efficient Distributed Learning for High-Dimensional Support Vector Machines," Mathematics, MDPI, vol. 10(7), pages 1-21, March.

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