plotts.true.wge: Plot of generated data, true autocorrelations and true spectral density for ARMA model

Description

For a given ARMA model, this function plots a realization, the true autocorrelations, and the true spectral density. This plot is typical of many plots in Applied Time Series Analysis by Woodward, Gray, and Elliott. For example, see Figure 1.21 and Figure 3.23.

Usage

plotts.true.wge(n=100, phi=0, theta=0, lag.max=25, mu=0,vara = 1,sn=0,plot.data=TRUE)

Value

data: Realization of length n that is generated from the ARMA model
aut1: True autocorrelations from the ARMA model for lags 0 to lag.max
acv: True autocovariances from the ARMA model for lags 0 to lag.max
spec: Spectral density (in dB) for the ARMA model calculated at frequencies f=0, .002, .004, ...., .5

Arguments

n: Length of time series realization to be generated. Default is 100
phi: Vector containing AR parameters
theta: Vector containing MA parameters
lag.max: Maximum lag for calculating and plotting autocorrelations
mu: True mean
vara: White noise variance: default=1
sn: determines the seed used in the simulation of plotted realization. sn=0 produces new/random realization each time. sn=positive integer produces same realization each time
plot.data: Logical variable: If TRUE a simulated realization is plotted

Author

Wayne Woodward

References

"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Examples

Run this code

plotts.true.wge(n=100, phi=c(1.6,-.9), theta=.8, lag.max=25, vara = 1)

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