Component Identification and Estimation in Nonlinear High-Dimensional Regression Models by Structural Adaptation
This article proposes a new method of analysis of a partially linear model whose nonlinear component is completely unknown. The target of analysis is identification of the set of regressors that enter in a nonlinear way in the model function, and complete estimation of the model, including slope coefficients of the linear component and the link function of the nonlinear component The procedure also allows selection of the significant regression variables. We also develop a test of linear...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the American Statistical Association|
|01_Samarov_Component_Identification_and_2005.pdf||494.3 kB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.