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refund (version 0.1-11)

Regression with Functional Data

Description

Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.

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Version

Install

install.packages('refund')

Monthly Downloads

2,224

Version

0.1-11

License

GPL (>= 2)

Maintainer

Lei Huang

Last Published

June 28th, 2014

Functions in refund (0.1-11)

Construct a function-on-function regression term

Construct a PC-based function-on-function regression term

Obtain residuals for a pffr fit

Plot PC-based function-on-function regression terms

Construct an FLM regression term

Function-on-scalar regression

Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function

Two-step function-on-scalar regression

refund-internal

Internal functions for the refund package

Functional principal component analysis by a two-stage method

Functional principal component analysis with fast covariance estimation

Longitudinal penalized functional regression

Leave-one-function-out cross-validation

pffr-constructor for functional principal component-based functional random intercepts.

Likelihood Ratio Test and Restricted Likelihood Ratio Test for inference of functional predictors

Octane numbers and NIR spectra of gasoline

Return call with all possible arguments

Functional principal components analysis by smoothed covariance

Summary for a pffr fit

Smoothed FPCA via iterative penalized rank one SVDs.

Prediction from a fitted FGAM model

Observed CD4 cell counts

Functional principal component regression

Penalized functional regression and Longitudinal penalized functional regression

Additive model with constraints

Penalized function-on-function regression with non-i.i.d. residuals

Plot a pffr fit

Regression with Functional Data

Get estimated coefficients from a pffr fit

Corrected confidence bands using functional principal components

smooth.construct.pcre.smooth.spec

mgcv-style constructor for PC-basis functional random effects

Longitudinal Functional Models with Structured Penalties

Obtain fitted values for a pffr fit

Simple bootstrap CIs for pffr

Penalized function-on-function regression

Generalized elastic net in the wavelet domain

Permutation test for wavelet-domain scalar-on-function regression

Pointwise cross-validation for function-on-scalar regression

Plotting of estimated regression functions obtained through lpeer()

Diffusion Tensor Imaging: tract profiles and outcomes

model.matrix.pffr

Obtain model matrix for a pffr fit

Functional Models with Structured Penalties

Default plotting for functional principal component regression output

Construct a smooth function-on-function regression term

print.summary.pffr

Print method for summary of a pffr fit

Plotting of estimated regression functions obtained through peer()

Sandwich smoother for matrix data

Default plotting for wavelet-domain scalar-on-function regression

Diffusion Tensor Imaging: more fractional anisotropy profiles and outcomes

Construct an FGAM regression term

Principal component regression and partial least squares in the wavelet domain

Permutation testing for function-on-scalar regression

Functional Generalized Additive Models

Simulate example data for pffr

Visualization of FGAM objects

Default plotting of function-on-scalar regression objects

smooth.construct.pss.smooth.spec

P-spline constructor with modified 'shrinkage' penalty

Prediction for penalized functional regression

Prediction method for generalized elastic net in the wavelet domain

Prediction for penalized function-on-function regression