autopairs

Bivariate time series plots: scatterplots, directed lines and kernel density
estimations using functions in the sm package.

Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics is available when the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests can be conducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).

Matthieu Stigler

tsDyn

Nonlinear Time Series Models with Regime Switching

Antonio Fabio Di Narzo

Jose Luis Aznarte

autopairs function

<dl><dt>x</dt>
<dd>time series</dd>
<dt>lag</dt>
<dd>time lag</dd>
<dt>h</dt>
<dd>kernel window (useful only for kernel estimations)</dd>
<dt>type</dt>
<dd>type of plot: contour levels, perspective plots, image, directed
lines, points or points with superposed kernel regression</dd></dl>

Arguments

Wrappers to sm by Antonio, Fabio Di Narzo

Author

Bivariate time series plots — autopairs

<dl>

<dt>x</dt>
<dd>time series</dd>


<dt>lag</dt>
<dd>time lag</dd>


<dt>h</dt>
<dd>kernel window (useful only for kernel estimations)</dd>


<dt>type</dt>
<dd>type of plot: contour levels, perspective plots, image, directed
lines, points or points with superposed kernel regression</dd>

</dl>

autopairs: Bivariate time series plots

Description

Usage

Value

Arguments

Author

Details

See Also

Examples