Data-driven ridge regression for Aalen’s additive risk model

Audrey Boruvka, Glen Takahara and Dongsheng Tu

Statistics & Probability Letters, 2016, vol. 109, issue C, 189-193

Abstract: Two data-driven procedures, based respectively on the L-curve and generalized cross-validation, are proposed for ridge regression under Aalen’s additive risk model. Monte Carlo simulations show that the L-curve is a useful criterion for identifying a nominal degree of regularization that appreciably reduces variance, particularly in smaller samples.

Keywords: Additive risk model; Event history data; L-curve; Mean square error; Ridge regression; Survival analysis (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1016/j.spl.2015.11.010

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