Interface  Description 

ARMAFit 
This interface represents a fitting method for estimating φ, θ, μ, σ^{2} in an ARMA model.

Class  Description 

ARMAForecast 
Forecasts an ARMA time series using the innovative algorithm.

ARMAForecastMultiStep 
Computes the hstep ahead prediction of a causal ARMA model, by the innovative algorithm.

ARMAForecastOneStep 
Computes the onestep ahead prediction of a causal ARMA model, by the innovative algorithm.

ARMAModel 
A univariate ARMA model, X_{t}, takes this form.

ARMAXModel 
The ARMAX model (ARIMA model with eXogenous inputs) is a generalization of the ARMA model by incorporating exogenous variables.

ARModel 
This class represents an AR model.

AutoCorrelation 
Compute the AutoCorrelation Function (ACF) for an AutoRegressive Moving Average (ARMA) model, assuming that
EX_{t} = 0.

AutoCovariance 
Computes the AutoCoVariance Function (ACVF) for an AutoRegressive Moving Average (ARMA) model by
recursion.

ConditionalSumOfSquares 
The method Conditional Sum of Squares (CSS) fits an ARIMA model by minimizing the conditional sum
of squares.

LinearRepresentation 
The linear representation of an Autoregressive Moving Average (ARMA) model is a (truncated) infinite sum of AR terms.

MAModel 
This class represents a univariate MA model.

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