forecast.ctree: Predict method for RTREE Model Fits

In macs: Recursive Partitioning Based Multivariate Adaptive Regression Models, Classification Trees, Survival Trees

Description

Predicted values based on RTREE model object.

Usage

  ## S3 method for class 'ctree'
forecast(object, newdata, ...)

Arguments

object	Object of class inheriting from "ctree"
newdata	An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used.
...	Further arguments to be passed to forecast.ctree

Details

forecast.ctree produces predicted values, obtained by evaluating the function tarv and rtree in the frame newdata.

Value

predictor	result of prediction for each row.
node	each value matches the ordinal number of terminal node.

See Also

The model fitting function tarv and rtree

Examples

# load "macs" library
library("macs")

# construct RTREE model
set.seed(1234)
data <- data.frame(y = sample(1:3, 1000, replace = TRUE),
                   n = as.factor(sample(1:4, 1000, replace = TRUE,
                                        prob = c(0.1, 0.3, 0.2, 0.4))),
                   o1 = sample(1:50, 1000, replace = TRUE),
                   o2 = sample(1:30, 1000, replace = TRUE),
                   o3 = sample(1:10, 1000, replace = TRUE),
                   o4 = sample(1:60, 1000, replace = TRUE),
                   o5 = sample(1:20, 1000, replace = TRUE),
                   o6 = sample(1:40, 1000, replace = TRUE))
head(data)
result <- rtree(data, method = "entropy", alpha = 0.01, cost = c(1, 1, 1))
result

# predictions
forecast(result, data[1:10, 2:8])

macs documentation built on Oct. 9, 2019, 5:05 p.m.