refund
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.
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")
.