Fits a Pareto distribution to the distribution of weights and calculates a quantile on the fitted model as classification threshold.
gpdEst(Wdata, thresh = -Inf, quantil = 0.95)A numeric vector representing weights of record pairs.
Threshold for exceedances.
A real number between 0 and 1. The desired quantil.
A real number representing the resulting classification threshold. It is assured that the threshold lies in a reasonable range.
The weights that exceed thresh are fitted to a
generalized Pareto distribution (GPD). The estimated parameters shape
and scale are used to calculate a classification threshold by the
formula
$$\mathit{thresh}+\frac{\mathit{scale}}{\mathit{shape}}
((\frac{n}{k}(1-\mathit{quantil}))^{-\mathit{shape}} -1)$$
where \(n\) is the total number of weights and \(k\) the number of
exceedances.
getParetoThreshold for user-level function