README.md

In xiaotiand/FunFor: Random Forest for Functional Data (FunFor)

FunFor

An R package for the functional random forest (FunFor) algorithm. The FunFor algorithm is able to predict curve responses for new observations and select important variables from a large set of scalar predictors.

The package can be installed by running:

devtools::install_github("xiaotiand/FunFor")

Then run

library(FunFor)

?FunFor

to get an example.

Also, see ?optimal_size for how to determine the optimal size of a tree fit. See ?predict.mvRF for how to predict from new observations based on a fitted FunFor model.

The typical running time of a FunFor model on data with sample size n=100, number of scalar predictors p=100, and length of functional curves T=100 is about 276s (4.6min).

system.time(FunFor(formula, data, mtry = 40, ntree = 10, npc = 3, m_split = 10))

user system elapsed

272.636 2.296 275.159

Citations:

Fu, G., Dai, X., & Liang, Y. (2021). Functional random forests for curve response. Scientific Reports, 11(1), 1-14.

xiaotiand/FunFor documentation built on Dec. 23, 2021, 6:18 p.m.