plot.bvpot {evd} | R Documentation |
Four plots (selectable by which
) are currently provided:
a density plot (1), a dependence function plot (2), a quantile
curves plot (3) and a spectral density plot (4).
Plot diagnostics for the generalized Pareto peaks-over-threshold
margins (selectable by mar
and which
) are also
available.
## S3 method for class 'bvpot': plot(x, mar = 0, which = 1:4, main, ask = nb.fig < length(which) && dev.interactive(), grid = 50, above = FALSE, levels = NULL, tlty = 1, blty = 3, rev = FALSE, p = seq(0.75, 0.95, 0.05), half = FALSE, ...)
x |
An object of class "bvpot" . |
mar |
If mar = 1 or mar = 2 diagnostics
are given for the first or second generalized Pareto
margin respectively. |
which |
A subset of the numbers 1:4 selecting
the plots to be shown. By default all are plotted. |
main |
Title of each plot. If given, should be a
character vector with the same length as which . |
ask |
Logical; if TRUE , the user is asked before
each plot. |
grid, levels |
Arguments for the density plot. The
data is plotted with a contour plot of the bivariate density
of the fitted model in the tail region. The density is evaluated
at grid^2 points, and contours are plotted at the values
given in the numeric vector levels . If levels is
NULL (the default), the routine attempts to find sensible
values. |
above |
Logical; if TRUE , only data points above
both marginal thresholds are plotted. |
tlty |
Line type for the lines identifying the thresholds. |
rev, blty |
Arguments to the dependence function
plot. See abvevd . |
p |
Lower tail probabilities for the quantile curves plot.
The plot is of the same type as given by the function
qcbvnonpar , but applied to the parametric
bivariate threshold model. |
half |
Argument to the spectral density plot. See
hbvevd . |
... |
Other arguments to be passed through to plotting functions. |
plot.bvevd
, contour
,
abvnonpar
, qcbvnonpar
bvdata <- rbvevd(500, dep = 0.6, model = "log") M1 <- fbvpot(bvdata, threshold = c(0,0), model = "log") ## Not run: plot(M1) ## Not run: plot(M1, mar = 1) ## Not run: plot(M1, mar = 2)