×

Nonlinear structure analysis with partial least-squares regression based on spline transformations. (Chinese. English summary) Zbl 1164.62362

Summary: A nonlinear partial least-squares regression model based on spline transformations not only takes advantages of the characters of spline functions which can locally fit continuous curves properly, but also brings in a partial least-squares regression method which can effectively solve the problem of high correlations in the set of independent variables.
In this paper, according to additive modeling methods both in theory and simulation, it is proven that nonlinear partial least-squares regression methods based on spline transformations can not only only the exact whole forecasting model, but also successfully extract nonlinear features of each independent variables’ effect on the dependent variable when dealing with nonlinear data systems with multi-absolute independent variables for one dependent variable. In this way, the complex nonlinear structures of the data system and an explainable model can be acquired.

MSC:

62J02 General nonlinear regression
62-07 Data analysis (statistics) (MSC2010)
PDFBibTeX XMLCite