GEV_shape_plot {qrmtools} | R Documentation |
Fit GEVs to block maxima and plot the fitted GPD shape as a function of the block size.
GEV_shape_plot(x, blocksize = tail(pretty(seq_len(length(x)/20), n = 64), -1), estimate.cov = TRUE, conf.level = 0.95, lines.args = list(lty = 2), xlab = "Block size", ylab = NULL, xlab2 = "Number of blocks", plot = TRUE, ...)
x |
|
blocksize |
|
estimate.cov |
|
conf.level |
confidence level of the confidence intervals if
|
lines.args |
|
xlab |
x-axis label. |
ylab |
y-axis label (if |
xlab2 |
label of the secondary x-axis. |
plot |
|
... |
additional arguments passed to the underlying
|
Such plots can be used in the block maxima method for determining the optimal block size (as the smallest after which the plot is (roughly) stable).
Invisibly returns a list
containing the block sizes
considered, the corresponding block maxima and the fitted GEV
distribution objects as returned by the underlying
fit_GEV_MLE()
.
Marius Hofert
set.seed(271) X <- rPar(5e4, shape = 4) GEV_shape_plot(X) abline(h = 1/4, lty = 3) # theoretical xi = 1/shape for Pareto