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npregfast: Nonparametric Estimation of Regression Models with Factor-by-Curve Interactions

npregfast is an R package for obtain nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers or splines. Additionally, a parametric model (allometric model) can be estimated. Particular features of the package are facilities for fast smoothness estimation, and the calculation of their first and second derivative. Users can define the smoothers parameters. Confidence intervals calculation is provided by bootstrap methods. Binning techniques were applied to speed up computation in the estimation and testing processes.

You can view a live interactive demo to see part of its capabilities at http://sestelo.shinyapps.io/npregfast.

Installation

npregfast is available through both CRAN and GitHub.

Get the released version from CRAN:

install.packages("npregfast")

Or the development version from GitHub:

# install.packages("devtools")
devtools::install_github("sestelo/npregfast")

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Version

Install

install.packages('npregfast')

Monthly Downloads

320

Version

1.3.0

License

MIT + file LICENSE

Maintainer

Marta Sestelo

Last Published

April 29th, 2016

Functions in npregfast (1.3.0)

plot.frfast

Visualization of frfast objects
runExample

Run npregfast example
allotest

Bootstrap based test for testing an allometric model
criticaldiff

Differences between the critical points for two factor's levels
plotdiff

Visualization of the differences between the estimated curves for two factor's levels
children

Children dataset.
globaltest

Testing the equality of the M curves specific to each level
critical

Critical points of the regression function
summary.frfast

Summarizing fits of frfast class
barnacle

Barnacle dataset.
localtest

Testing the equality of critical points
npregfast

npregfast: Nonparametric Estimation of Regression Models with Factor-by-Curve Interactions.
frfast

Fitting nonparametric models
predict.frfast

Prediction from fitted frfast model