Description Usage Arguments Methods Examples
Allows the user to use functionality provided by ForecastFramework with sarimaTD models.
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data A data set to fit sarimaTD models to, in a format compatible with
ForecastFramework::IncidenceMatrix
frequency frequency of time series. Must be provided if y is not
of class "ts". See the help for stats::ts for more.
transformation character specifying transformation type:
"box-cox", "log", "forecast-box-cox", or "none". See details of
sarimaTD::fit_sarima for more.
seasonal_difference boolean; take a seasonal difference before passing
to auto.arima?
newdata new data from which to predict forward, in a format compatible
with ForecastFramework::IncidenceMatrix
steps If TRUE, force the Python process to terminate
using a system call.
nsim Number of simulations to generate during forecasting
$new() Initialize a sarimaTD model object.
$fit() Fit a set of models to the provided data, one model per
location.
$forecast() Generate forecasts for each location.
$data() Get the data set used for the model fit.
$nsim() Get or set the number of simulations to generate during
forecasting.
$frequency() Get the time series frequency of the data used for the
model fit.
$transformation() Get the transformation performed before fitting the
model.
$seasonal_difference() Get the indicator of whether or not first-order
seasonal differencing is performed before fitting the model.
$models() Get a list of sarimaTD model fit objects, one for each
location in the training data.
1 | vignette(package="sarimaTD", topic="sarimaTD_FF")
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