Functional regression

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Functional regression

Functional regression is an extension of the traditional multivariate regression with scalar responses and scalar covariates, which allows one to conduct regression analysis on functional data. One the one hand, functional regression models can be classified into three types based 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, partially linear, or nonlinear. In particular, functional polynomial models, functional single and multiple single models and functional additive models are three special cases of functional nonlinear models.

Functional linear models (FLMs)

Functional linear models (FLMs) are an extension of traditional multivariate linear models with scalar response Failed to parse (syntax error): {\displaystyle Y∈ℝ} and scalar covariates