plotts.sample.wge: Plot Data, Sample Autocorrelations, Periodogram, and Parzen...

In tswge: Time Series for Data Science

Plot Data, Sample Autocorrelations, Periodogram, and Parzen Spectral Estimate

Description

For a given realization, this function plots the data, and calculates and plots the sample autocorrelations, periodogram, and Parzen window spectral estimator in a 2x2 array of plots.

Usage

plotts.sample.wge(x, lag.max = 25, trunc = 0, arlimits=FALSE,speclimits=c(0,0),
periodogram=FALSE)

Arguments

x	A vector containing the realization
lag.max	The maximum lag at which to calculate the sample autocorrelations
trunc	The truncation point M for the Parzen spectral estimator. If M=0 theN M=2sqrt(n). If M>0 then M is the value entered
arlimits	Logical variable. TRUE plots 95 percent limit lines on sample autocorrelation plots
periodogram	Logical variable. TRUE plots periodogram, default=FALSE
speclimits	User supplied limits for Parzen spectral density and periodogram, default=function decides limits

Value

xbar	The sample mean of the realization
autplt	A vector containing sample autocorrelations from 0, 1, ..., aut.lag
freq	A vector containing the frequencies at which the periodogram and window estimate are calculated
db	Periodogram (in dB) calculated at the frequecies in freq
freq	Parzen spectral estimate (in dB) calculated at the frequecies in freq

Author(s)

Wayne Woodward

References

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

Examples

data(wages)
plotts.sample.wge(wages,trunc=0)

tswge documentation built on Feb. 16, 2023, 6:51 p.m.