garma_gen: Generate from generalized ARMA

In TYtianyang/tsms: Modeling Univariate Time Series with Multiple Seasonality

Description

Generate a sample series from a specified generalized ARMA model.

Usage

garma.gen(n, U, p, q, S1 = NULL, S2 = NULL, phi = NULL, psi = NULL, tau1 = NULL, tau2 = NULL, noise = 1)

Arguments

n	length of series
U	number of data points burned-in
p	number of regular AR components
q	number of regular MA components
S1	a set of lag orders of additional AR components
S2	a set of lag orders of additional MA components
phi	coefficients of regular AR components
psi	coefficients of regular MA components
tau1	coefficients of additional AR components
tau2	coefficients of additional MA components
noise	standard deviation of white noise

Details

Please note that the generator will automatically filter the generated series: those diverge dramatically will be ignored. However, it still does not gaurantee stationarity.

Value

X	generated series in a n by 1 matrix
p	number of regular AR components
q	number of regular MA components
S1	a set of lag orders of additional AR components
S2	a set of lag orders of additional MA components
beta	coefficients vector

Author(s)

Tianyang Xie

TYtianyang/tsms documentation built on Sept. 10, 2020, 1:54 p.m.