true.arma.aut.wge

R function to calculate the autocovariances and autocorrelations and optionally plot the true autocorrelations of a stationary ARMA model

 ARMA 

 Autocorrelations 

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

true.arma.aut.wge function

<dl>
 
 <dt>phi</dt>
<dd>Vector containing AR coefficients</dd> <dt>theta</dt>
<dd>Vector containing MA coefficients</dd> <dt>lag.max</dt>
<dd>Maximum lag at which to calculate the true autocorrelations</dd> <dt>vara</dt>
<dd>White noise variance of the ARMA model</dd> <dt>plot</dt>
<dd>Logical: TRUE=plot, FALSE=no plot</dd></dl>

Arguments

Author

True ARMA autocorrelations — true.arma.aut.wge

<dl>
 
 <dt>phi</dt>
<dd>Vector containing AR coefficients</dd>

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

 <dt>lag.max</dt>
<dd>Maximum lag at which to calculate the true autocorrelations</dd>

 <dt>vara</dt>
<dd>White noise variance of the ARMA model</dd>

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

</dl>

true.arma.aut.wge: True ARMA autocorrelations

Description

Usage

Value

Arguments

Author

References

Examples