getcoef.hd

the object obtained from <code><a rd-options="" href="/link/cv.hd?package=FRegSigCom&version=0.3.0" data-mini-rdoc="FRegSigCom::cv.hd">cv.hd</a></code>.

fit.cv

This function is used to calculate the estimates for \(\mu(t), \beta_i(s,t)\) based on the object obtained from <code><a rd-options="" href="/link/cv.hd?package=FRegSigCom&version=0.3.0" data-mini-rdoc="FRegSigCom::cv.hd">cv.hd</a></code>.

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.

Ruiyan Luo

FRegSigCom

Functional Regression using Signal Compression Approach

getcoef.hd function

the object obtained from <code><a rd-options='' href='cv.hd'>cv.hd</a></code>.

This function is used to calculate the estimates for \(\mu(t), \beta_i(s,t)\) based on the object obtained from <code><a rd-options='' href='cv.hd'>cv.hd</a></code>.

Get the estimated coefficient functions for linear function-on-function models with a large numbe of predictor curves
 — getcoef.hd

Get the estimated coefficient functions for linear function-on-function models with a large numbe of predictor curves

getcoef.hd: Get the estimated coefficient functions for linear function-on-function models with a large numbe of predictor curves

Description

Usage

Arguments

Value

See Also

Examples