Takes a series of i.
Takes a series of i.i.d. observations and returns a time series based on it with the time-dependent effects of this model added.
Time series of i.i.d. observations.
Array to put the filtered series, can be the same as ts.
The dest series, for convenience.
The constant term.
The constant term in the variance.
The autoregressive term.
Takes a time series that is assumed to have this model's characteristics and returns a time series with time-dependent effects of this model removed.
Takes a time series that is assumed to have this model's characteristics and returns a time series with time-dependent effects of this model removed.
This is the inverse of TimeSeriesModel#addTimeDependentEffects.
Time series of observations with this model's characteristics.
Array to put the filtered series, can be the same as ts.
The dest series, for convenience.
Samples a random time series of a given length with the properties of the model.
Samples a random time series of a given length with the properties of the model.
The length of the time series to sample.
The random generator used to generate the observations.
The samples time series.
A GARCH(1, 1) + AR(1) model, where y(i) = c + phi * y(i - 1) + eta(i), and h(i), the variance of eta(i), is given by h(i) = omega + alpha * eta(i) ** 2 + beta * h(i - 1) ** 2