ggacf

a numeric vector or an object of the <code>ts</code> class containing a stationary time series.

title

Plot of the auto-correlation function for a univariate time series.

Despite that several tests for normality in stationary processes have been proposed
in the literature, consistent implementations of these tests in programming languages are limited.
Four normality test are implemented. The Lobato and Velasco's, Epps, Psaradakis and  Vavra, and the
random projections tests for stationary process. Some other diagnostics such as, unit root test for
stationarity, seasonal tests for seasonality, and arch effect test for volatility; are also performed.
The package also offers residual diagnostic for linear time series models developed in several packages.

Asael Alonzo Matamoros

nortsTest

Assessing Normality of Stationary Process

Alicia Nieto-Reyes

Rob Hyndman

Mitchell O'Hara-Wild

Trapletti A.

ggacf function

<dl><dt>y</dt>
<dd>a numeric vector or an object of the <code>ts</code> class containing a stationary time series.</dd>
<dt>title</dt>
<dd>a string with the plot's title.</dd></dl>

Arguments

Author

acf plot — ggacf

<dl>

<dt>y</dt>
<dd>a numeric vector or an object of the <code>ts</code> class containing a stationary time series.</dd>


<dt>title</dt>
<dd>a string with the plot's title.</dd>

</dl>

ggacf: `acf` plot

Description

Usage

Value

Arguments

Author

Examples