# specar.ci: Confidence interval for the ar-spectrum and the dominant... In nlts: (Non)Linear Time Series Analysis

## 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)

`plot.specar.ci` `summary.specar.ci`
 ```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) ```