# spec.ar

0th

Percentile

##### Estimate Spectral Density of a Time Series from AR Fit

Fits an AR model to x (or uses the existing fit) and computes (and by default plots) the spectral density of the fitted model.

Keywords
ts
##### Usage
spec.ar(x, n.freq, order = NULL, plot = TRUE, na.action = na.fail,
method = "yule-walker", …)
##### Arguments
x

A univariate (not yet:or multivariate) time series or the result of a fit by ar.

n.freq

The number of points at which to plot.

order

The order of the AR model to be fitted. If omitted, the order is chosen by AIC.

plot

Plot the periodogram?

na.action

NA action function.

method

method for ar fit.

Graphical arguments passed to plot.spec.

##### Value

An object of class "spec". The result is returned invisibly if plot is true.

##### Note

The multivariate case is not yet implemented.

##### Warning

Some authors, for example Thomson (1990), warn strongly that AR spectra can be misleading.

##### References

Thompson, D.J. (1990). Time series analysis of Holocene climate data. Philosophical Transactions of the Royal Society of London Series A, 330, 601--616. http://www.jstor.org/stable/53609.

Venables, W.N. and Ripley, B.D. (2002) Modern Applied Statistics with S. Fourth edition. Springer. (Especially page 402.)

ar, spectrum.
library(stats) # NOT RUN { require(graphics) spec.ar(lh) spec.ar(ldeaths) spec.ar(ldeaths, method = "burg") spec.ar(log(lynx)) spec.ar(log(lynx), method = "burg", add = TRUE, col = "purple") spec.ar(log(lynx), method = "mle", add = TRUE, col = "forest green") spec.ar(log(lynx), method = "ols", add = TRUE, col = "blue") # }