simts (version 0.2.2)

GM: Create a Gauss-Markov (GM) Process

Description

Sets up the necessary backend for the GM process.

Usage

GM(beta = NULL, sigma2_gm = 1)

Value

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

process.desc

Used in summary: "BETA","SIGMA2"

theta

\(\beta\), \(\sigma ^2_{gm}\)

plength

Number of parameters

print

String containing simplified model

desc

"GM"

obj.desc

Depth of parameters e.g. list(1,1)

starting

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

Arguments

beta

A double value for the \(\beta\) of an GM process (see Note for details).

sigma2_gm

A double value for the variance, \(\sigma ^2_{gm}\), of a GM process (see Note for details).

Author

James Balamuta

Details

When supplying values for \(\beta\) and \(\sigma ^2_{gm}\), these parameters should be of a GM process and NOT of an AR1. That is, do not supply AR1 parameters such as \(\phi\), \(\sigma^2\).

Internally, GM parameters are converted to AR1 using the `freq` supplied when creating data objects (gts) or specifying a `freq` parameter in simts or simts.imu.

The `freq` of a data object takes precedence over the `freq` set when modeling.

Examples

GM()
GM(beta=.32, sigma2_gm=1.3)