Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
On the foundations of parameter estimation for generalized partial linear models with B-splines and continuous optimization
Date
2010-07-01
Author
TAYLAN, PAKİZE
Weber, Gerhard Wilhelm
Liu, Lian
Yerlikaya-Ozkurt, Fatma
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
211
views
0
downloads
Cite This
Generalized linear models are widely used in statistical techniques. As an extension, generalized partial linear models utilize semiparametric methods and augment the usual parametric terms with 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 the penalized maximum likelihood and 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 have come to constitute an important complementary approach, alternative to the penalty methods, with flexibility for choosing the penalty parameter adaptively. In particular, we model and treat the constrained P-IRIS problem by using the elegant framework of conic quadratic programming. The method is illustrated using a small numerical example.
Subject Keywords
Modelling and Simulation
,
Computational Theory and Mathematics
,
Computational Mathematics
URI
https://hdl.handle.net/11511/56919
Journal
COMPUTERS & MATHEMATICS WITH APPLICATIONS
DOI
https://doi.org/10.1016/j.camwa.2010.04.040
Collections
Graduate School of Applied Mathematics, Article
Suggestions
OpenMETU
Core
On disconjugacy and stability criteria for discrete Hamiltonian systems
Mert, R.; Zafer, Ağacık (Elsevier BV, 2011-10-01)
By making use of new Lyapunov type inequalities, we establish disconjugacy and stability criteria for discrete Hamiltonian systems. The stability criteria are given when the system is periodic.
On periodic solutions of differential equations with piecewise constant argument
Akhmet, Marat (Elsevier BV, 2008-10-01)
The periodic quasilinear system of differential equations with small parameter and piecewise constant argument of generalized type [M.U. Akhmet, Integral manifolds of differential equations with piecewise constant argument of generalized type, Nonlinear Anal. TMA, 66 (2007) 367-383, M.U. Akhmet, On the reduction principle for differential equations with piecewise argument of generalized type, J. Math. Anal. Appl. 336 (2007) 646-663] is addressed. We consider the critical case, when associated linear homogen...
ON FOUNDATIONS OF PARAMETER ESTIMATION FOR GENERALIZED PARTIAL LINEAR MODELS WITH B-SPLINES AND CONTINUOUS OPTIMIZATION
TAYLAN, PAKİZE; Weber, Gerhard Wilhelm; Liu, Lian (2010-02-04)
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...
Analysis of variance and linear contrasts in experimental design with generalized secant hyperbolic distribution
Yilmaz, Yidiz E.; Akkaya, Ayşen (Elsevier BV, 2008-07-01)
We consider one-way classification model in experimental design when the errors have generalized secant hyperbolic distribution. We obtain efficient and robust estimators for block effects by using the modified maximum likelihood estimation (MML) methodology. A test statistic analogous to the normal-theory F statistic is defined to test block effects. We also define a test statistic for testing linear contrasts. It is shown that test statistics based on MML estimators are efficient and robust. The methodolo...
Oscillation of solutions of second order mixed nonlinear differential equations under impulsive perturbations
ÖZBEKLER, ABDULLAH; Zafer, Ağacık (Elsevier BV, 2011-02-01)
New oscillation criteria are obtained for second order forced mixed nonlinear impulsive differential equations of the form
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
P. TAYLAN, G. W. Weber, L. Liu, and F. Yerlikaya-Ozkurt, “On the foundations of parameter estimation for generalized partial linear models with B-splines and continuous optimization,”
COMPUTERS & MATHEMATICS WITH APPLICATIONS
, pp. 134–143, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56919.