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Original Articles

Penalized Maximum Likelihood Principle for Choosing Ridge Parameter

Pages 1610-1624 | Received 03 Jan 2009, Accepted 19 May 2009, Published online: 07 Jul 2009

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Read on this site (3)

Yan Shen & Zhenlin Yang. (2015) Bias-correction for Weibull common shape estimation. Journal of Statistical Computation and Simulation 85:15, pages 3017-3046.
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Funda Erdugan & Fikri Akdeniz. (2012) Computational Method for Jackknifed Generalized Ridge Tuning Parameter based on Generalized Maximum Entropy. Communications in Statistics - Simulation and Computation 41:8, pages 1411-1429.
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Pedro Macedo, Manuel Scotto & Elvira Silva. (2010) On the Choice of the Ridge Parameter: A Maximum Entropy Approach. Communications in Statistics - Simulation and Computation 39:8, pages 1628-1638.
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Articles from other publishers (3)

Kristoffer H. Hellton & Nils Lid Hjort. (2018) Fridge: Focused fine-tuning of ridge regression for personalized predictions. Statistics in Medicine 37:8, pages 1290-1303.
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Rosa J. Meijer & Jelle J. Goeman. (2013) Efficient approximate k -fold and leave-one-out cross-validation for ridge regression . Biometrical Journal 55:2, pages 141-155.
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MINH‐NGOC TRAN. (2011) The Loss Rank Criterion for Variable Selection in Linear Regression Analysis. Scandinavian Journal of Statistics 38:3, pages 466-479.
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