View source: R/mcpot-simmcpot.R
simmcpot | R Documentation |
Simulate a synthetic Markov chain from a fitted 'mcpot'
object.
simmcpot(object, plot = TRUE, ...)
object |
An object of class |
plot |
Logical. If |
... |
Other optional arguments to be passed to the
|
The simulated Markov chain is computed as follows:
Simulate a Markov chain prob
with uniform margins on
(0,1) and with the fixed extreme value dependence given by
object
;
For all prob
such as prob <= 1
- pat, set mc = NA (where pat
is given by
object$pat
);
For all prob
such as prob >= 1
- pat, set prob2 = (prob
- 1 + pat) / pat. Thus, prob2
are uniformly distributed on
(0,1);
For all prob2
, set mc = qgpd(prob2, thresh,
scale, shape)
, where thresh, scale, shape
are given by the
object$threshold, object$param["scale"]
and
object$param["shape"]
respectively.
A Markov chain which has the same features as the fitted object. If
plot = TRUE
, the Markov chain is plotted.
Mathieu Ribatet
fitmcgpd
, simmc
data(ardieres) flows <- ardieres[,"obs"] Mclog <- fitmcgpd(flows, 5) par(mfrow = c(1,2)) idx <- which(flows <= 5) flows[idx] <- NA plot(flows, main = "Ardieres Data") flowsSynth <- simmcpot(Mclog, main = "Simulated Data")
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