linear: Linear AutoRegressive models

In tsDyn: Nonlinear Time Series Models with Regime Switching

Linear AutoRegressive models

Description

AR(m) model

Usage

	linear(x, m, d=1, steps=d, series, include = c( "const", "trend","none", "both"), 
        type=c("level", "diff", "ADF"), warn_root=TRUE)

Arguments

x	time series
m, d, steps	embedding dimension, time delay, forecasting steps
series	time series name (optional)
include	Type of deterministic regressors to include
type	Whether the variable is taken is level, difference or a mix (diff y= y-1, diff lags) as in the ADF test
warn_root	Whether to check (and warn) for roots outside the unit circle?

Details

AR(m) model:

x_{t+s} = \phi_0 + \phi_1 x_t + \phi_2 x_{t-d} + \dots + \phi_m x_{t - (m-1)d} + \epsilon_{t+s}

Value

A nlar object, linear subclass.

Author(s)

Antonio, Fabio Di Narzo

See Also

nlar for fitting this and other models to time series data

Examples

#fit an AR(2) model
mod.linear <- linear(log(lynx), m=2)
mod.linear
summary(mod.linear)

tsDyn documentation built on Oct. 31, 2024, 5:08 p.m.