plotts.true.wge {tswge}

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)

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

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

Note

gvar=g[1], i.e. autocovariance at lag 0

Author(s)

Wayne Woodward

References

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

Examples

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