pot function

Peaks Over Thresholds Model

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,
    ...)

Arguments

• 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

Returns

An object of class "potd" describing the fit and including parameter estimates and standard errors.

Details

Uses optim for point process likelihood maximization.

See Also

gpd, plot.potd, plot.gpd, decluster, optim, as.POSIXct

Examples

data(danish)
out <- pot(danish, 10)  
# Fits POT model to Danish fire insurance losses