forecast.stree: Predict method for STREE 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 'stree'
forecast(object, newdata, ...)

Arguments

object	Object of class inheriting from "stree"
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.stree

Details

forecast.stree produces predicted values, obtained by evaluating the function stree 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 stree

Examples

# load "macs" library
library("macs")
set.seed(1234)
data <- data.frame(r = runif(1000, 1, 10), c = rbinom(1000, 1, 0.5),
                   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 <-  stree(data, family = "likelihood")
result

# predictions
forecast(result, data[1:10, 3:9])

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