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]>
LicenseGPL-2
Version0.3.0
URL http://sites.gsu.edu/rluo/ http://sites.gsu.edu/xqi3/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("FRegSigCom")

Try the FRegSigCom package in your browser

Any scripts or data that you put into this service are public.

FRegSigCom documentation built on May 1, 2019, 9:45 p.m.