gen_sarima: Generate Seasonal Autoregressive Order P - Moving Average...

In SMAC-Group/gmwm: Generalized Method of Wavelet Moments

Description

Generate an ARMA(P,Q) process with supplied vector of Autoregressive Coefficients (φ), Moving Average Coefficients (θ), and σ^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 σ^2 parameter is indeed a variance parameter. This differs from R's use of the standard deviation, σ.

Value

A vec that contains the generated observations.

Examples

gen_sarima(10, c(.3,.5), 1, c(.1), c(.2), 0, c(.4), 1, 12, 0)

SMAC-Group/gmwm documentation built on Sept. 11, 2021, 10:06 a.m.