gen_arima: Generate Autoregressive Order p, Integrated d, Moving Average...

In SMAC-Group/simts: Time Series Analysis Tools

Generate Autoregressive Order p, Integrated d, Moving Average Order q (ARIMA(p,d,q)) Model

Description

Generate an ARIMA(p,d,q) process with supplied vector of Autoregressive Coefficients (\phi), Integrated d, Moving Average Coefficients (\theta), and \sigma^2.

Usage

gen_arima(N, ar, d, ma, sigma2 = 1.5, n_start = 0L)

Arguments

N	An integer for signal length.
ar	A vec that contains the AR coefficients.
d	An integer that indicates a difference.
ma	A vec that contains the MA coefficients.
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.

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.

Value

A vec that contains the generated observations.

Warning

Please note, this function will generate a sum of N + d number of observations, where d denotes the number of differences necessary.

SMAC-Group/simts documentation built on Sept. 4, 2023, 5:25 a.m.