fore.garma.wge

Find forecasts using a specified GARMA model

 GARMA 

 Gegenbauer 

 forecasts 

Accompanies the texts Time Series for Data Science with R by Woodward, Sadler and Robertson & Applied Time Series Analysis with R, 2nd edition by Woodward, Gray, and Elliott.  It is helpful for data analysis and for time series instruction.

Bivin Sadler

tswge

Time Series for Data Science

fore.garma.wge function

<dl> <dt>x</dt>
<dd>Realization to be analyzed</dd> <dt>u</dt>
<dd>Parameter u in GARMA model</dd> <dt>lambda</dt>
<dd>Parameter lambda in GARMA model</dd> <dt>phi</dt>
<dd>Coefficients of the AR component of the GARMA model</dd> <dt>theta</dt>
<dd>Coefficients of the MA component of the GARMA model</dd> <dt>n.ahead</dt>
<dd>Number of values to forecast</dd> <dt>lastn</dt>
<dd>If lastn=TRUE then the last n.ahead values are forecast. Otherwise, if lastn=FALSE the next n.ahead values are forecast</dd> <dt>plot</dt>
<dd>If plot=TRUE then plots of the data and forecasts are plotted</dd></dl>

Arguments

Author

Forecast using a GARMA model — fore.garma.wge

<dl>

 <dt>x</dt>
<dd>Realization to be analyzed</dd>

 <dt>u</dt>
<dd>Parameter u in GARMA model</dd>

 <dt>lambda</dt>
<dd>Parameter lambda in GARMA model</dd>

 <dt>phi</dt>
<dd>Coefficients of the AR component of the GARMA model</dd>

 <dt>theta</dt>
<dd>Coefficients of the MA component of the GARMA model</dd>

 <dt>n.ahead</dt>
<dd>Number of values to forecast</dd>

 <dt>lastn</dt>
<dd>If lastn=TRUE then the last n.ahead values are forecast. Otherwise, if lastn=FALSE the next n.ahead values are forecast</dd>

 <dt>plot</dt>
<dd>If plot=TRUE then plots of the data and forecasts are plotted</dd>

</dl>

fore.garma.wge: Forecast using a GARMA model

Description

Usage

Value

Arguments

Author

Details

References

Examples