windowf(timeslab)R Documentation

Calculate Nonparamteric Spectral Density Estimate

Description

Calculate Nonparamteric Spectral Density Estimate

Usage

windowf(rho,R0,Q,ioptw,M,n,alpha=0.05)

Arguments

rho Array of length {M} (if {ioptw} is between 1 and 5) or length ${tt{n}}-1$ if {ioptw} is between 6 and 8 containing autocorrelations.
R0 Real scalar containing the sample variance $(>0)$.
Q Integer containing the number of frequencies between 0 and 1 at which to calculate spectra.
ioptw Integer containing the number of the window to be used in the estimation procedure as indicated by the following:
1 ~~ Truncated periodogram
2 ~~ Bartlett
3 ~~ Tukey
4 ~~ Parzen
5 ~~ Bohman
6 ~~ Daniell
7 ~~ Bartlett–Priestley
8 ~~ Parzen–Cogburn–Davis
M Integer $(>0)$ containing scale parameter.
n (If either {ioptw} is between 6 and 8 or the factor for determining confidence intervals is desired.) Integer containing the length of the data set being analyzed.
alpha Real scalar ($0<${alpha}$<1$) indicating the level of confidence.

Value

f Array of length $[{tt{Q}}/2]+1$ containing the spectral estimator at the frequencies $(j-1)/{tt{Q}},j=1,...,[{tt{Q}}/2]+1$.
c Real scalar variable that can be used to find 95% confidence intervals for the true spectral density. The interval at the $i$th frequency would be from {f(i)/c} to {f(i)*c}.


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