STIC.RFimpute {streamDAG} | R Documentation |
A wrapper for missForest for random forest STIC imputation
Description
A simple wrapper for the missForest
random forest imputation algorithm. STIC.RFimpute
first converts STIC (Stream Temperature, Intermittency, and Conductivity) presence/absence data to categorical outcomes to avoid regression fitting. One should consult missForest
for specifics on the underlying algorithm.
Usage
STIC.RFimpute(p.a, ...)
Arguments
p.a |
Optimally, a dataframe containing presence absence data at sites (columns) over time (rows). |
... |
Additional arguments from |
Value
Provides the conventional unaltered missForest
output.
Author(s)
Daniel J. Stekhoven, <stekhoven@stat.math.ethz.ch>
References
Stekhoven, D.J. and Buehlmann, P. (2012), 'MissForest - nonparametric missing value imputation for mixed-type data', Bioinformatics, 28(1) 2012, 112-118, doi: 10.1093/bioinformatics/btr597
Examples
arc.pa <- data.frame(matrix(ncol = 3, data = c(1,1,1, 0,1,1, 1,1,1, 0,NA,1), byrow = TRUE))
names(arc.pa) <- c("n1 --> n2", "n2 --> n3", "n3 --> n4")
STIC.RFimpute(arc.pa)
[Package streamDAG version 1.5-9 Index]