hresiduals.tsissm.estimate {tsissm} | R Documentation |
Multi-Step Ahead In-Sample Residuals
Description
Extract the multi-step ahead in-sample residual values from an estimated model.
Usage
## S3 method for class 'tsissm.estimate'
hresiduals(
object,
h = 12,
transformed = TRUE,
index_start = 0,
simplify = TRUE,
...
)
hresiduals(object, ...)
Arguments
object |
an object of class “tsissm.estimate”. |
h |
the forecast horizon |
transformed |
residuals based values in transformed space (Box Cox). |
index_start |
the time point from which to initiate the in-sample rolling forecasts. This is zero based to enable the first forecast to be t=1. |
simplify |
whether to return a matrix type data.table of error against date and horizon, else the long for data.table with the forecasts, actuals and errors. |
... |
not currently used. |
Details
For each time point t (t>=index_start), in the data sample, an h-steps ahead forecast (predicting the observation at time t + h) is made, using the full sample estimated parameters and observed data up to t. These h-step-ahead fitted residuals, in either transformed or untransformed space, can sometimes be used for diagnosing the multi-step ahead in-sample performance of the model. This is not a substitute for a proper rolling out of sample forecast, but a quick method which may still be useful.
Value
A data.table in either long or wide format.