Spline based sparseness and smoothness for partially nonlinear model via c-fused lasso
Yükleniyor...
Tarih
2025
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
American Institute of Mathematical Sciences
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
One of the most beneficial and widely used models for data analysis are partially nonlinear models (PNLRM), which consists of parametric and nonparametric components. Since the model includes the coefficients of both the parametric and nonparametric parts, the complexity of the model will be high and its interpretation will be very difficult. In this study, we propose a procedure that not only achieves sparseness, but also smoothness for PNLRM to obtain a simpler model that better explains the relationship between the response and covariates. Thus, the fused Lasso problem is taken into account where nonparametric components are expressed as a spline basis function, and then the Fused Lasso estimation problem is built and expressed in terms of conic quadratic programming. Applications are conducted to evaluate the performance of the proposed method by considering commonly utilized measures. Promising results are obtained, especially in the data with nonlinearly correlated variables.
Açıklama
Anahtar Kelimeler
Continuous optimization, Estimation, Fused Lasso, Nonlinear model, Nonparametric regression, Spline function
Kaynak
Journal of Industrial and Management Optimization
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
21
Sayı
2
Künye
Taylan, P., Yerlikaya, F. Ö. ve Tez, M. (2025). Spline based sparseness and smoothness for partially nonlinear model via c-fused lasso. Journal of Industrial and Management Optimization, 21(2), 1120-1144.
