Evaluate the Approximate Confidence Interval of a mvEWS Estimate
Evaluate the Approximate Confidence Interval of a mvEWS Estimate
Evaluate the approximate confidence interval of a multivariate evolutionary wavelet spectrum.
methods
ApxCI(object, var =NULL, alpha =0.05,...)
Arguments
object: A mvLSW object containing the multivariate evolutionary wavelet spectrum estimate.
var: A mvLSW object containing the variance estimate of the wavelet spectrum. If this is NULL (default) then the variance is estimates by calling the varEWS and using object.
alpha: Type I error, a single numerical value within (0,0.5].
...: Additional arguments to be passed to the varEWS command.
Details
The command evaluates the approximate Gaussian confidence intervals for the elements of the mvEWS estimate.
Returns
Invisibly returns a list containing two mvLSW classed objects with names "L" and "U" that respectively identify the lower and upper interval estimates.
References
Taylor, S.A.C., Park, T.A. and Eckley, I. (2019) Multivariate locally stationary wavelet analysis with the mvLSW R package. Journal of statistical software 90 (11) pp. 1--16, doi: 10.18637/jss.v090.i11.
Park, T. (2014) Wavelet Methods for Multivariate Nonstationary Time Series, PhD thesis, Lancaster University, pp. 91-111.
See Also
mvEWS, as.mvLSW, varEWS.
Examples
## Define evolutionary wavelet spectrum, structure only on level 2Spec <- array(0, dim = c(3,3,8,256))Spec[1,1,2,]<-10Spec[2,2,2,]<- c(rep(5,64), rep(0.6,64), rep(5,128))Spec[3,3,2,]<- c(rep(2,128), rep(8,128))Spec[2,1,2,]<- Spec[1,2,2,]<- punif(1:256,65,192)Spec[3,1,2,]<- Spec[1,3,2,]<- c(rep(-1,128), rep(5,128))Spec[3,2,2,]<- Spec[2,3,2,]<--0.5EWS <- as.mvLSW(x = Spec, filter.number =1, family ="DaubExPhase", min.eig.val =NA)## Sample time series and estimate the EWS.set.seed(10)X <- rmvLSW(Spectrum = EWS)EWS_X <- mvEWS(X, kernel.name ="daniell", kernel.param =20)## Evaluate asymptotic spectral variance SpecVar <- varEWS(EWS_X)## Plot Estimate & 95% confidence intervalCI <- ApxCI(object = EWS_X, var = SpecVar, alpha =0.05)plot(x = EWS_X, style =2, info =2, Interval = CI)