print.smoots

This function regulates how objects created by the package <code>smoots</code> are
printed.

The nonparametric trend and its derivatives in equidistant time
series (TS) with short-memory stationary errors can be estimated. The
estimation is conducted via local polynomial regression using an
automatically selected bandwidth obtained by a built-in iterative plug-in
algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel
smoother is also built-in as a comparison. With version 1.1.0, a linearity
test for the trend function, forecasting methods and backtesting
approaches are implemented as well.
The smoothing methods of the package are described in Feng, Y., Gries, T.,
and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598>.

Dominik Schulz

smoots

Nonparametric Estimation of the Trend and Its Derivatives in TS

Yuanhua Feng

Sebastian Letmathe

Thomas Gries

Marlon Fritz

print.smoots function

<dl><dt>x</dt>
<dd>an input object of class <code>smoots</code>.</dd>
<dt>...</dt>
<dd>included for compatibility; additional arguments will however
not affect the output.</dd></dl>

Arguments

<ul>
<li>Dominik Schulz (Research Assistant) (Department of Economics, Paderborn
University), 
Package Creator and Maintainer</li>
</ul>

Author

Print Method for the Package 'smoots' — print.smoots

<dl>

<dt>x</dt>
<dd>an input object of class <code>smoots</code>.</dd>


<dt>...</dt>
<dd>included for compatibility; additional arguments will however
not affect the output.</dd>

</dl>

<ul>
<li>Dominik Schulz (Research Assistant) (Department of Economics, Paderborn
University), 
Package Creator and Maintainer</li>
</ul>

print.smoots: Print Method for the Package 'smoots'

Description

Usage

Value

Arguments

Author