Confidence interval for the ar-spectrum and the dominant period.

Share:

Description

A funcion 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

1
2
3
    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 var-covar 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.

Author(s)

Ottar N. Bjornstad onb1@psu.edu

See Also

plot.specar.ci summary.specar.ci

Examples

1
2
3
4
5
6
7
8
9
   data(plodia)


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

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

    summary.specar.ci(fit)
 

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.