quantregForest {quantregForest}R Documentation

Quantile Regression Forests

Description

Quantile Regression Forests infer conditional quantile functions from data

Usage

quantregForest(x, y, mtry = ceiling(ncol(x)/3), nodesize = 10, ntree = 1000)

Arguments

x A matrix or data.frame containing the predictor variables
y The response variable; a numerical vector
mtry The number of variables to try for each split; same default setting as for Random Forests
nodesize The minimal number of instances in each terminal node; the default setting is slightly higher than for Random Forests
ntree The number of trees to be grown

Details

It might be useful to try various values of mtry and see which one works best; however, results are typically not heavily dependent on this parameter.

Value

A value of class quantregForest, for which print, plot, and predict methods are available.

Author(s)

Nicolai Meinshausen

References

N. Meinshausen (2006) "Quantile Regression Forests", Journal of Machine Learning Research 7, 983-999 http://jmlr.csail.mit.edu/papers/v7/

See Also

For prediction, see predict.quantregForest

Examples


################################################
##  Load air-quality data (and preprocessing) ##
################################################

data(airquality)
set.seed(1)

## remove observations with mising values
airquality <- airquality[ !apply(is.na(airquality), 1,any), ]

## number of remining samples
n <- nrow(airquality)

## divide into training and test data
indextrain <- sample(1:n,round(0.6*n),replace=FALSE)
Xtrain     <- airquality[ indextrain,2:6]
Xtest      <- airquality[-indextrain,2:6]
Ytrain     <- airquality[ indextrain,1]
Ytest      <- airquality[-indextrain,1]


################################################
##     compute Quantile Regression Forests    ##
################################################

qrf <- quantregForest(x=Xtrain, y=Ytrain)

## plot out-of-bag predictions for the training data
plot(qrf)

## compute out-of-bag predictions 
quant.outofbag <- predict(qrf)

## predict test data
quant.newdata  <- predict(qrf, newdata= Xtest)



[Package quantregForest version 0.2-2 Index]