plot.MCSSA: Plot Monte Carlo SSA In simsalabim: A collection of methods for time series analysis and signal detection.

Description

Plots SSA - eigenspectrum and draws monte carlo error bars for each eigenvalue.

Usage

 ```1 2 3 4 5``` ```## S3 method for class 'MCSSA' plot(x, by = "freq", normalize = FALSE, asFreq = TRUE, lam.pch = 19, lam.col = "black", lam.cex = 1, sig.col = "red", sig.pch = 19, sig.cex = 1, conf.col = "darkgray", log = "xy", ann = TRUE, legend = TRUE, axes = TRUE, ...) ```

Arguments

 `x` output of `MCSSA`. `by` How to order the eigenvalues. `"freq"`: by frequency. `"rank"`: by their rank (decreasingly ordered). `normalize` Normalise eigenvalues by their sum. `asFreq` If `by="freq"`, shall the frequency be expressed as “frequency” or as “period”. `lam.pch` `pch` of the eigenvalues. `lam.col` `col` of the eigenvalues. `lam.cex` `cex` of the eigenvalues. `sig.col` `col` of the significant eigenvalues. `sig.pch` `pch` of the significant eigenvalues. `sig.cex` `cex` of the significant eigenvalues. `conf.col` `col` of the monte carlo confidence limits. `log` Use logarithmic axes, usage like `log` in `par`. `ann` Whether to do annotations or not. `legend` Whether to produce a legend or not. `axes` Whether to draw axes or not. `...` Further arguments to be passed to graphical functions.

Details

Eigenvalues larger than the upper bound of the monte carlo confidence limits are considered to be not explainable by an AR1 noise process.

Author(s)

Lukas Gudmundsson

`MCSSA`, `par`