Trimmed mean estimator
Estimate the shape parameter of a Pareto distribution using a trimmed mean approach.
a numeric vector.
the number of observations in the upper tail to which the Pareto distribution is fitted.
the threshold (scale parameter) above which the Pareto distribution is fitted.
A numeric vector of length two giving the trimming proportions for the lower and upper end of the tail, respectively. If a single numeric value is supplied, it is recycled.
x0 of course correspond with each other.
k is supplied, the threshold
x0 is estimated with the n
- k largest value in
x, where n is the number of observations.
On the other hand, if the threshold
x0 is supplied,
k is given
by the number of observations in
x larger than
x0 needs to be supplied. If both are supplied,
k is used (mainly for back compatibility).
The estimated shape parameter.
x0 for the threshold (scale parameter) of the
Pareto distribution was introduced in version 0.2.
Andreas Alfons and Josef Holzer
Brazauskas, V. and Serfling, R. (2000) Robust estimation of tail parameters for two-parameter Pareto and exponential models via generalized quantile statistics. Extremes, 3(3), 231–249.
Brazauskas, V. and Serfling, R. (2000) Robust and efficient estimation of the tail index of a single-parameter Pareto distribution. North American Actuarial Journal, 4(4), 12–27.
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data(eusilc) # equivalized disposable income is equal for each household # member, therefore only one household member is taken eusilc <- eusilc[!duplicated(eusilc$db030),] # estimate threshold ts <- paretoScale(eusilc$eqIncome, w = eusilc$db090) # using number of observations in tail thetaTM(eusilc$eqIncome, k = ts$k) # using threshold thetaTM(eusilc$eqIncome, x0 = ts$x0)
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