| pot {evir} | R Documentation |
Fits a Poisson point process to the data, an approach
sometimes known as peaks over thresholds (POT), and
returns an object of class "potd".
pot(data, threshold = NA, nextremes = NA, run = NA, picture = TRUE,
...)
data |
numeric vector of data, which may have a times
attribute containing (in an object of class "POSIXct", or
an object that can be converted to that class; see
as.POSIXct) the times/dates of each observation.
If no times attribute exists, the data are assumed to
be equally spaced. |
threshold |
a threshold value (either this or nextremes
must be given but not both) |
nextremes |
the number of upper extremes to be used (either
this or threshold must be given but not both) |
run |
if the data are to be declustered the run length
parameter for the runs method (see decluster)
should be entered here |
picture |
whether or not a picture should be drawn if declustering is performed |
... |
arguments passed to optim |
Uses optim for point process likelihood maximization.
An object of class "potd" describing the fit and including
parameter estimates and standard errors.
gpd, plot.potd,
plot.gpd, decluster,
optim, as.POSIXct
data(danish) out <- pot(danish, 10) # Fits POT model to Danish fire insurance losses