2010
Penalized regression with individual deviance effects
Publication
Publication
Computational Statistics , Volume 25 - Issue 2 p. 341- 361
The present work addresses the problem of model estimation and computations for discrete data when some covariates are modeled smoothly using splines. We propose to introduce and explicitly estimate individual deviance effects (one for each observation), constrained by a ridge penalty. This turns out to be an effective way to absorb model excess variation and detect systematic patterns. Large but very sparse systems of penalized likelihood equations have to be solved. We present fast and compact algorithms for fitting, estimation and computation of the effective dimension. Applications to counts, binomial, and survival data illustrate practical use of this model.
| Additional Metadata | |
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| , , , | |
| doi.org/10.1007/s00180-009-0180-x, hdl.handle.net/1765/26943 | |
| Computational Statistics | |
| Organisation | Erasmus MC: University Medical Center Rotterdam |
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Perperoglou, A., & Eilers, P. (2010). Penalized regression with individual deviance effects. Computational Statistics, 25(2), 341–361. doi:10.1007/s00180-009-0180-x |
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