README.md

In refunders/refund: Regression with Functional Data

refund

Methods for regression with functional data

These packages implement various approaches to functional data regression.

Regression with scalar responses and functional predictors is implemented in functions pfr, peer, lpeer, fpcr and fgam. For regression with functional responses, see pffr, fosr, and fosr2s.

Regularized covariance and FPC estimation is implemented in functions fpca.sc, fpca.ssvd, fpca.face, fpca2s.

Shiny-based interactive graphics for visualizing results from fpca and regression methods in refund can be generated using the plot_shiny() function in the refund.shiny package.

Wavelet-based functional regression methods with scalar responses and functional predictors can be found in the wcr and wnet functions in the refund.wave package.

Installation

To install the latest patched version directly from Github, please use devtools::install_github("refunders/refund") for refund and devtools::install_github("refunders/refund.shiny") for refund.shiny and devtools::install_github("refunders/refund.wave") for refund.wave.

To install the developer version with experimental features directly from Github, please use devtools::install_github("refunders/refund", ref="devel").

refunders/refund documentation built on March 20, 2024, 7:11 a.m.