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refund (version 0.1-8)

refund: 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

4,424

Version

0.1-8

License

GPL (>= 2)

Maintainer

Lei Huang

Last Published

July 18th, 2013

Functions in refund (0.1-8)

Obtain fitted values for a pffr fit

Functional principal component regression

Sandwich smoother for matrix data

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

Return call with all possible arguments

Functional principal component analysis by a two-stage method

Corrected confidence bands using functional principal components

Function-on-scalar regression

Simple bootstrap CIs for pffr

Leave-one-function-out cross-validation

Generalized elastic net in the wavelet domain

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

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

smooth.construct.pcre.smooth.spec

mgcv-style constructor for PC-basis functional random effects

Octane numbers and NIR spectra of gasoline

Simulate example data for pffr

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

Permutation testing for function-on-scalar regression

Construct an FLM regression term

smooth.construct.pss.smooth.spec

P-spline constructor with modified 'shrinkage' penalty

Diffusion Tensor Imaging: more fractional anisotropy profiles and outcomes

print.summary.pffr

Print method for summary of a pffr fit

Prediction for penalized functional regression

Functional Models with Structured Penalties

Default plotting of function-on-scalar regression objects

Obtain residuals for a pffr fit

Longitudinal penalized functional regression

Smoothed FPCA via iterative penalized rank one SVDs.

Functional principal components analysis by smoothed covariance

Penalized functional regression and Longitudinal penalized functional regression

Functional principal component analysis with fast covariance estimation

Penalized function-on-function regression

Observed CD4 cell counts

Prediction from a fitted FGAM model

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

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

Regression with Functional Data

Pointwise cross-validation for function-on-scalar regression

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

Construct a function-on-function regression term

Two-step function-on-scalar regression

Functional Generalized Additive Models

model.matrix.pffr

Obtain model matrix for a pffr fit

Plot a pffr fit

Additive model with constraints

Summary for a pffr fit

Construct a smooth function-on-function regression term

Principal component regression and partial least squares in the wavelet domain

Prediction for penalized function-on-function regression

Visualization of FGAM objects

refund-internal

Internal functions for the refund package

Plot PC-based function-on-function regression terms

Plotting of estimated regression functions obtained through peer()

Prediction method for generalized elastic net in the wavelet domain

Diffusion Tensor Imaging: fractional anisotropy profiles and outcomes

Construct an FGAM regression term

Get estimated coefficients from a pffr fit

Longitudinal Functional Models with Structured Penalties

Default plotting for functional principal component regression output

Plotting of estimated regression functions obtained through lpeer()