AR: Create an Autoregressive P [AR(P)] Process

In simts: Time Series Analysis Tools

Create an Autoregressive P [AR(P)] Process

Description

Sets up the necessary backend for the AR(P) process.

Usage

AR(phi = NULL, sigma2 = 1)

Arguments

phi	A vector with double values for the \phi of an AR(P) process (see Note for details).
sigma2	A double value for the variance, \sigma ^2, of an AR(P) process. (see Note for details).

Value

An S3 object with called ts.model with the following structure:

process.desc

Used in summary: "AR-1","AR-2", ..., "AR-P", "SIGMA2"

theta

\phi_1, \phi_2, ..., \phi_p, \sigma^2

plength

Number of Parameters

desc

"AR"

print

String containing simplified model

obj.desc

Depth of Parameters e.g. list(p,1)

starting

Guess starting values? TRUE or FALSE (e.g. specified value)

Note

We consider the following model:

X_t = \sum_{j = 1}^p \phi_j X_{t-1} + \varepsilon_t

, where \varepsilon_t is iid from a zero mean normal distribution with variance \sigma^2.

Author(s)

James Balamuta

Examples

AR(1) # Slower version of AR1()
AR(phi=.32, sigma=1.3) # Slower version of AR1()
AR(2) # Equivalent to ARMA(2,0).

simts documentation built on Aug. 31, 2023, 5:07 p.m.