windowf(timeslab) | R Documentation |
Calculate Nonparamteric Spectral Density Estimate
windowf(rho,R0,Q,ioptw,M,n,alpha=0.05)
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 ~~ BartlettPriestley |
|
8 ~~ ParzenCogburnDavis |
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. |
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 }. |