gen_generic_sarima: Generate Generic Seasonal Autoregressive Order P - Moving...

In schoi355/gmwm: Generalized Method of Wavelet Moments

Generate Generic 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 (φ), Moving Average Coefficients (θ), and σ^2.

Usage

gen_generic_sarima(N, theta_values, objdesc, sigma2 = 1.5,
  n_start = 0L)

Arguments

N	An integer for signal length.
theta_values	A vec containing the parameters for (S)AR and (S)MA.
objdesc	A vec that contains the +.ts.model's obj.desc field.
sigma2	A double that contains process variance.
n_start	An unsigned int that indicates the amount of observations to be used for the burn in period.
s	An integer that contains a seasonal id.

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)

schoi355/gmwm documentation built on April 11, 2022, 1:21 a.m.