ON FOUNDATIONS OF PARAMETER ESTIMATION FOR GENERALIZED PARTIAL LINEAR MODELS WITH B-SPLINES AND CONTINUOUS OPTIMIZATION
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Tarih
2010
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Amer Inst Physics
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Generalized linear models are widely-used statistical techniques. As an extension, generalized partial linear models utilize semiparametric methods and augment the usual parametric terms by a single nonparametric component of a continuous covariate. In this paper, after a short introduction, we present our model in the generalized additive context with a focus on penalized maximum likelihood and on the penalized iteratively reweighted least squares (P-IRLS) problem based on B-splines which is attractive for nonparametric components. Then, we approach solving the P-IRLS problem using continuous optimization techniques. They become an important complementary technology and alternative to the penalty methods with the flexibility of choosing the penalty parameter adaptively. In particular, we model and treat the constrained P-IRLS problem by the elegant framework of conic quadratic programming. This paper is of a more theoretical nature and a preparation of real-world applications in future.
Açıklama
3rd Global Conference on Power Control and Optimization -- FEB 02-04, 2010 -- Gold Coast, AUSTRALIA
Anahtar Kelimeler
Regression, Generalized Linear Models, Generalized Partial Linear Models, Generalized Additive Model, Least Squares, Maximum Likelihood, Curvature, Newton-Rapshon Algorithm, Penalty Methods, Continuous Optimization, Conic Quadratic Programming
Kaynak
Power Control and Optimization
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
1239
