forecast.spdur {spduration} | R Documentation |
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 |
... |
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 |
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)