gen_sarima: Generate Seasonal Autoregressive Order P - Moving Average...
In SMAC-Group/simts: Time Series Analysis Tools

gen_sarima

R Documentation

Generate Seasonal Autoregressive Order P - Moving Average Order Q (SARMA(p,q)x(P,Q)) Model

Description

Generate an ARMA(P,Q) process with supplied vector of Autoregressive Coefficients (\phi), Moving Average Coefficients (\theta), and \sigma^2.

Usage

gen_sarima(N, ar, d, ma, sar, sd, sma, sigma2 = 1.5, s = 12L, n_start = 0L)

Arguments

`N`	An `integer` for signal length.
`ar`	A `vec` that contains the AR coefficients.
`d`	An `integer` that indicates a non-seasonal difference.
`ma`	A `vec` that contains the MA coefficients.
`sar`	A `vec` that contains the SAR coefficients.
`sd`	An `integer` that indicates a seasonal difference.
`sma`	A `vec` that contains the SMA coefficients.
`sigma2`	A `double` that contains process variance.
`s`	An `integer` that contains a seasonal id.
`n_start`	An `unsigned int` that indicates the amount of observations to be used for the burn in period.

Details

The innovations are generated from a normal distribution. The \sigma^2 parameter is indeed a variance parameter. This differs from R's use of the standard deviation, \sigma.