Estimation in the partially nonlinear model by continuous optimization

Yerlikaya-Ozkurt F., Taylan P., TEZ M.

JOURNAL OF APPLIED STATISTICS, vol.48, no.13-15, pp.2826-2846, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 13-15
  • Publication Date: 2021
  • Doi Number: 10.1080/02664763.2020.1864816
  • Journal Name: JOURNAL OF APPLIED STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Veterinary Science Database, zbMATH
  • Page Numbers: pp.2826-2846
  • Keywords: Nonlinear model, nonparametric regression, estimation, B-spline, continuous optimization, FINANCE
  • Marmara University Affiliated: Yes

Abstract

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.