FRegSigCom: Functional Regression using Signal Compression Approach

Signal compression methods for functional regression. It includes various function-on-function (FOF) regression models such as the linear FOF model with functional response and both scalar and functional predictors for a small number of functional predictors, linear FOF models with a large number of functional predictors, linear FOF model for spiky data, stepwise selection for FOF models with two-way interactions, and nonlinear FOF models. It also includes scalar-on-function regression models with single (SOF) or multivariate (mSOF) scalar response variable, and SOF model for spiky data.

Getting started

Package details

AuthorRuiyan Luo, Xin Qi
MaintainerRuiyan Luo <[email protected]>
Package repositoryView on CRAN
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FRegSigCom documentation built on May 1, 2019, 9:45 p.m.