Description Usage Arguments Value References See Also Examples
This function calculates wavelet variance confidence intervals for the unbiased and block averaged discrete wavelet variance estimates. Given var{tau(j)} are the time independent unbiased wavelet variance estimates at scales tau(j) where j are the decomposition levels, the approximate 100(1-2p)% confidence interval is given by
[n * var{tau(j)} / Q(1-p), n * var{tau(j)} / Q(p)]
where Q(p) is the p x 100 percentage point for a chi-squared distribution with n degrees of freedom distribution.
1 | wavVarConfidence(wvar, edof, probability=0.95)
|
wvar |
a vector containing the block-averaged unbiased wavelet variance estimates. |
edof |
a vector containing the equivalent degrees of freedom estimates. See |
probability |
the probability desired for the confidence
intervals. Supported probabilities are 0.005, .025, .05, .95, .975, and .995. Default: |
a list of the low and high confidence interval limits for levels 1,..., J.
D. B. Percival and A. T. Walden, Wavelet Methods for Time Series Analysis, Cambridge University Press, 2000.
1 2 3 4 5 6 | ## first calculate the EDOF for the ocean series
edof <- wavEDOF(ocean)
## calculate the 95% confidence intervals for EDOF
## mode 1
wavVarConfidence(edof$variance.unbiased, edof$EDOF1)
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