specar.ci: Confidence interval for the ar-spectrum and the dominant...

In nlts: Nonlinear Time Series Analysis

Description

A function to estimate a "confidence interval" for the power spectrum and in particular a confidence interval for the dominant period. The function uses resampling of the autoregressive parameters to attain the estimate.

Usage

specar.ci(x, order, resamp = 500, nfreq = 100, echo = TRUE)

Arguments

x	A time series without missing values.
order	a scalar representing the order to be considered. If "aic" the orderis be selected automatically using the AIC criterion.
resamp	the number of resamples of the ar-coefficients from the covariance matrix.
nfreq	the number of points at which to save the value for the power spectrum (and confidence envelope).
echo	If TRUE, a counter for each nrun shows the progress.

Details

A "confidence interval" for the periodogram is obtained by resampling the ar-coefficients using the variance-covariance matrix from the ar.mle object.

If a zero'th order process is chosen by using the AIC criterion, a first order process will be used.

If the dynamics is highly nonlinear, the parametric estimate of the power spectrum may be inappropriate.

Value

An object of class "specar.ci" is returned consisting of the following components:

order	the ar-order.
spectrum$freq	the spectral frequencies.
spectrum$spec	the estimated power-spectrum of the data.
resamp$spectrum	gives the quantile summary for the resampling distribution of the spectral powers.
resamp$maxfreq	the full vector of output for the resampled max.frequencies.

See Also

plot.specar.ci summary.specar.ci

Examples

   data(plodia)


    fit <- specar.ci(sqrt(plodia), order=3, resamp=10) 

    ## Not run: plot(fit, period=FALSE)

    summary(fit)

nlts documentation built on May 1, 2019, 8:44 p.m.