forecast.spdur: Forecast from a spdur model

In spduration: Split-Population Duration (Cure) Regression

Forecast from a spdur model

Description

forecast method for spdur class objects.

Usage

## S3 method for class 'spdur'
forecast(
  object,
  ...,
  pred.data = NULL,
  stat = "conditional hazard",
  n.ahead = 6
)

Arguments

object	A spdur class model object.
...	Optional arguments, not used.
pred.data	Data on which to base forecasts, i.e. slice of last time unit's observations for all cross-sectional units.
stat	Which statistic to forecast, see predict.spdur for possible options
n.ahead	How many time periods to predict ahead. Default is 6.

Details

This function will create out-of-sample predictions of “stat” using model estimates and the prediction data provided. It is assumed that prediction data consist of a slice of the last time period observed for the data used to estimate the model in object. For each row, forecast.spdur will estimate the model predictions for that time point and then extrapolate the resulting probability to n.ahead time periods using appropriate probability theory.

For situations in which the covariate values are known for future time periods, e.g. in a test sample use predict.spdur instead.

Examples

library(forecast)
data(coups)
data(model.coups)

coups.dur <- add_duration(coups, "succ.coup", "gwcode", "year", freq="year")
pred.data <- coups.dur[coups.dur$year==max(coups.dur$year), ]
pred.data <- pred.data[complete.cases(pred.data), ]
fcast <- forecast(model.coups, pred.data=pred.data)

spduration documentation built on May 29, 2024, 1:30 a.m.