Functional regression: Difference between revisions

Revision as of 03:25, 15 March 2017

Revision as of 04:32, 15 March 2017

Line 1:

{{User sandbox}}

<!-- EDIT BELOW THIS LINE -->

'''Functional regression''' is a version of [[Regression analysis|regression analysis]] when [[Dependent and independent variables|responses]] or [[Dependent and independent variables|covariates]] include [[Functional data analysis|functional data]]. On the one hand, functional regression models can be classified into four types depending on whether the responses or covariates are functional or scalar: (i) scalar responses with functional covariates, (ii) functional responses with scalar covariates, (iii) functional responses with functional covariates, and (iv) scalar or functional responses with functional and scalar covariates. On the other hand, functional regression models can be [[Linear regression|linear]], partially linear, or [[Nonlinear regression|nonlinear]]. In particular, functional polynomial models, functional [[Semiparametric_regression#Index_models|single and multiple singleindex models]] and functional [[Additive model|additive models]] are three special cases of functional nonlinear models.

__TOC__