gen.arma.wge

This function calls arima.sim but with more simple parameter structure for stationary ARMA models

 Realization 

 ARMA 

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.arma.wge function

<dl> <dt>n</dt>
<dd>Length of realization to be generated</dd> <dt>phi</dt>
<dd>Vector of AR coefficients</dd> <dt>theta</dt>
<dd>Vector of MA coefficients</dd> <dt>vara</dt>
<dd>White noise variance, default=1</dd> <dt>mu</dt>
<dd>Theoretical mean, default=0</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 an ARMA realization — gen.arma.wge

<dl>

 <dt>n</dt>
<dd>Length of realization to be generated</dd>

 <dt>phi</dt>
<dd>Vector of AR coefficients</dd>

 <dt>theta</dt>
<dd>Vector of MA coefficients</dd>

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

 <dt>mu</dt>
<dd>Theoretical mean, default=0</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.arma.wge: Function to generate an ARMA realization

Description

Usage

Value

Arguments

Author

References

Examples