Estimation in the partially nonlinear model by continuous optimization
Yükleniyor...
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Ltd.
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
A useful model for data analysis is the partially nonlinear model where response variable is represented as the sum of a nonparametric and a parametric component. In this study, we propose a new procedure for estimating the parameters in the partially nonlinear models. Therefore, we consider penalized profile nonlinear least square problem where nonparametric components are expressed as a B-spline basis function, and then estimation problem is expressed in terms of conic quadratic programming which is a continuous optimization problem and solved interior point method. An application study is conducted to evaluate the performance of the proposed method by considering some well-known performance measures. The results are compared against parametric nonlinear model.
Açıklama
Anahtar Kelimeler
B-spline, Continuous optimization, Estimation, Nonlinear model, Nonparametric regression
Kaynak
Journal of Applied Statistics
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
48
Sayı
13-15
Künye
Özkurt, F. Y., Taylan, P. ve Tez, M. (2021). Estimation in the partially nonlinear model by continuous optimization. Journal of Applied Statistics, 48(13-15), 2826-2846.
