| egp | R Documentation |
This function provides the log-likelihood and quantiles for the three different families presented
in Papastathopoulos and Tawn (2013). The latter include an additional parameter, \kappa.
All three families share the same tail index as the generalized Pareto distribution, while allowing for lower thresholds.
In the case \kappa=1, the models reduce to the generalised Pareto.
egp.retlev gives the return levels for the extended generalised Pareto distributions
xdat |
vector of observations, greater than the threshold |
thresh |
threshold value |
par |
parameter vector ( |
model |
a string indicating which extended family to fit |
show |
logical; if |
p |
extreme event probability; |
plot |
boolean indicating whether or not to plot the return levels |
For return levels, the p argument can be related to T year exceedances as follows:
if there are n_y observations per year, than take p
to equal 1/(Tn_y) to obtain the T-years return level.
egp.ll returns the log-likelihood value.
egp.retlev returns a plot of the return levels if plot=TRUE and a matrix of return levels.
egp.ll(xdat, thresh, par, model=c('egp1','egp2','egp3'))
egp.retlev(xdat, thresh, par, model=c('egp1','egp2','egp3'), p, plot=TRUE)
Leo Belzile
Papastathopoulos, I. and J. Tawn (2013). Extended generalised Pareto models for tail estimation, Journal of Statistical Planning and Inference 143(3), 131–143.
set.seed(123)
xdat <- mev::rgp(1000, loc = 0, scale = 2, shape = 0.5)
par <- fit.egp(xdat, thresh = 0, model = 'egp3')$par
p <- c(1/1000, 1/1500, 1/2000)
#With multiple thresholds
th <- c(0, 0.1, 0.2, 1)
opt <- tstab.egp(xdat, th, model = 'egp1')
egp.retlev(xdat, opt$thresh, opt$par, 'egp1', p = p)
opt <- tstab.egp(xdat, th, model = 'egp2', plots = NA)
egp.retlev(xdat, opt$thresh, opt$par, 'egp2', p = p)
opt <- tstab.egp(xdat, th, model = 'egp3', plots = NA)
egp.retlev(xdat, opt$thresh, opt$par, 'egp3', p = p)
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