gen.garma.wge

This function calls gen.geg.wge and arima.sim

 Realization 

 GARMA 

 Gegenbauer 

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

gen.garma.wge function

<dl> <dt>n</dt>
<dd>the realization length to be generated</dd> <dt>u</dt>
<dd>Parameter u in the GARMA model given in (11.16) of Woodward, Gray, and Elliott text</dd> <dt>lambda</dt>
<dd>Parameter lambda in the GARMA model given in (11.16) of Woodward, Gray, and Elliott text</dd> <dt>phi</dt>
<dd>vector of AR parameters of ARMA part of GARMA model</dd> <dt>theta</dt>
<dd>vector of MA parameters of ARMA part of GARMA model using signs as given ijn the Woodward, Grayu, and Elliott text</dd> <dt>trun</dt>
<dd>the truncation point of the infinite GLP form</dd> <dt>burn_in</dt>
<dd>is the burning-in period for the simulation</dd> <dt>vara</dt>
<dd>White noise variance, default=1</dd> <dt>plot</dt>
<dd>Logical: TRUE=plot, FALSE=no plot</dd> <dt>sn</dt>
<dd>determines the seed used in the simulation. sn=0 produces new/random realization each time. sn=positive integer produces same realization each time</dd></dl>

Arguments

Author

Function to generate a GARMA realization — gen.garma.wge

<dl>

 <dt>n</dt>
<dd>the realization length to be generated</dd>

 <dt>u</dt>
<dd>Parameter u in the GARMA model given in (11.16) of Woodward, Gray, and Elliott text</dd>

 <dt>lambda</dt>
<dd>Parameter lambda in the GARMA model given in (11.16) of Woodward, Gray, and Elliott text</dd>

 <dt>phi</dt>
<dd>vector of AR parameters of ARMA part of GARMA model</dd>

 <dt>theta</dt>
<dd>vector of MA parameters of ARMA part of GARMA model using signs as given ijn the Woodward, Grayu, and Elliott text</dd>

 <dt>trun</dt>
<dd>the truncation point of the infinite GLP form</dd>

 <dt>burn_in</dt>
<dd>is the burning-in period for the simulation</dd>

 <dt>vara</dt>
<dd>White noise variance, default=1</dd>

 <dt>plot</dt>
<dd>Logical: TRUE=plot, FALSE=no plot</dd>

 <dt>sn</dt>
<dd>determines the seed used in the simulation. sn=0 produces new/random realization each time. sn=positive integer produces same realization each time</dd>

</dl>

gen.garma.wge: Function to generate a GARMA realization

Description

Usage

Value

Arguments

Author

References

Examples