orders: Functions that extract values from the fitted model

Description

These functions allow extracting orders and lags for ssarima(), gum() and sma(), type of model from es() and ces() and name of model.

Usage

orders(object, ...)
lags(object, ...)
modelName(object, ...)
modelType(object, ...)

Arguments

object

Model estimated using one of the functions of smooth package.

...

Currently nothing is accepted via ellipsis.

Value

Either vector, scalar or list with values is returned. orders() in case of ssarima returns list of values:

ar - AR orders.
i - I orders.
ma - MA orders.

lags() returns the vector of lags of the model. All the other functions return strings of character.

Details

orders() and lags() are useful only for SSARIMA, GUM and SMA. They return NA for other functions. This can also be applied to arima(), Arima() and auto.arima() functions from stats and forecast packages. modelType() is useful only for ETS and CES. They return NA for other functions. This can also be applied to ets() function from forecast package. errorType extracts the type of error from the model (either additive or multiplicative). Finally, modelName returns the name of the fitted model. For example, "ARIMA(0,1,1)". This is purely descriptive and can also be applied to non-smooth classes, so that, for example, you can easily extract the name of the fitted AR model from ar() function from stats package.

Examples

Run this code

# NOT RUN {
x <- rnorm(100,0,1)

# Just as example. orders and lags do not return anything for ces() and es(). But modelType() does.
ourModel <- ces(x, h=10)
orders(ourModel)
lags(ourModel)
modelType(ourModel)
modelName(ourModel)

# And as another example it does the opposite for gum() and ssarima()
ourModel <- gum(x, h=10, orders=c(1,1), lags=c(1,4))
orders(ourModel)
lags(ourModel)
modelType(ourModel)
modelName(ourModel)

# Finally these values can be used for simulate functions or original functions.
ourModel <- auto.ssarima(x)
ssarima(x, orders=orders(ourModel), lags=lags(ourModel), constant=ourModel$constant)
sim.ssarima(orders=orders(ourModel), lags=lags(ourModel), constant=ourModel$constant)

ourModel <- es(x)
es(x, model=modelType(ourModel))
sim.es(model=modelType(ourModel))

# }