forecast.masal: Predict method for MASAL Model Fits

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

Description

Predicted values based on MASAL model object.

Usage

  ## S3 method for class 'masal'
forecast(object, newdata = NULL, col = NULL, ...)

Arguments

object	Object of class inheriting from "masal"
newdata	An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used.
col	A character vector indicating each column in the data : c(covariate), t(time), s(sort). If omitted, the fitted values are used.
...	Further arguments to be passed to forecast.masal

Details

forecast.masal produces predicted values, obtained by evaluating the regression function in the frame newdata.

Value

forecast.masal produces a vector of predictions for all rows.

See Also

The model fitting function masal.

Examples

library("macs")
set.seed(123)
data <- data.frame(ID = sort(rep(1:100, 5)),
                    X1 = runif(500, min = 0, max = 1),
                    X2 = runif(500, min = 0, max = 2),
                    X3 = runif(500, min = 0, max = 4),
                    X4 = rnorm(500, mean = 0, sd = 1),
                    X5 = rnorm(500, mean = 0, sd = 2),
                    X6 = rnorm(500, mean = 0, sd = 3),
                    time = rep(1:5, 100),
                    Y = rnorm(500, mean = 40, sd = 10))
result <- masal(data, col = NULL, maxterm = 20, maxinteraction = 2,
 varhat = c(1, 1, 1), forced_num = NULL, maxiter = 2)
forecast(result)

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