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

In schoi355/gmwm: Generalized Method of Wavelet Moments

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 (φ), Integrated d, Moving Average Coefficients (θ), and σ^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 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.

Warning

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

Examples

# Generate an ARIMA model
xt = gen_arima(10, c(.3,.5), 1, c(.1), 1.5, 0)

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