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This vignette explains how to use functions in legion
package, what they produce, what each field in outputs and what returned
values mean.
The package includes the following functions:
legion
There are several methods that can be used together with the
forecasting functions of the package. When a model is saved to some
object ourModel
, these function will do some magic. Here’s
the list of all the available methods with brief explanations:
print(ourModel)
– function prints brief output with
explanation of what was fitted, with what parameters, errors etc;summary(ourModel)
– alias for
print(ourModel)
;actuals(ourModel)
– returns actual values;fitted(ourModel)
– fitted values of the model;residuals(ourModel)
– residuals of constructed model;
AIC(ourModel)
, BIC(ourModel)
,
AICc(ourModel)
and BICc(ourModel)
–
information criteria of the constructed model. AICc()
and
BICc()
functions are not standard stats
functions and are imported from greybox
package and
modified in legion
for the specific models;plot(ourModel)
– produces plots for the diagnostics of
the constructed model. There are 9 options of what to produce, see
?plot.legion()
for more details. Prepare the canvas via
par(mfcol=...)
before using this function otherwise the
plotting might take time.forecast(ourModel)
– point and interval forecasts;plot(forecast(ourModel))
– produces graph with actuals,
forecast, fitted and prediction interval using graphmaker()
function from greybox
package.simulate(ourModel)
– produces data simulated from
provided model. Only works for ves()
for now;logLik(ourModel)
– returns log-likelihood of the
model;nobs(ourModel)
– returns number of observations
in-sample we had;nparam(ourModel)
– number of estimated parameters
(originally from greybox
package);nvariate(ourModel)
– number of variates, time series in
the model (originally from greybox
package);sigma(ourModel)
– covariance matrix of the residuals of
the model;modelType(ourModel)
– returns the type of the model.
Returns something like “MMM” for ETS(MMM). Can be used with
ves()
and vets()
. In the latter case can also
accept pic=TRUE
, returning the PIC restrictions;errorType(ourModel)
– the type of the error of a model
(additive or multiplicative);coef(ourModel)
– returns the vector of all the
estimated coefficients of the model;These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.