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Automated mean residual life plots

Source: R/mrl.R
thselect.mrl.Rd

This function implements the automated proposal from Section 2.2 of Langousis et al. (2016) for mean residual life plots. It returns the threshold that minimize the weighted mean square error and moment estimators for the scale and shape parameter based on weighted least squares.

Usage

thselect.mrl(xdat, thresh, kmax, plot = TRUE, ...)

Arguments

xdat

[numeric] vector of observations

thresh

[numeric] vector of thresholds; if missing, uses all order statistics from the 20th largest until kmax as candidates

kmax

[integer] maximum number of order statistics

plot

[logical] if TRUE (default), return a plot of the mean residual life plot with the fitted slope and the chosen threshold

...

additional arguments, currently ignored

Value

a list containing

  • thresh: candidate threshold vector

  • thresh0: selected threshold

  • scale: scale parameter estimate

  • shape: shape parameter estimate

  • mrl: empirical mean excess values

  • xdat: ordered observations

  • intercept: intercept for mean excess value at chosen threshold

  • slope: slope for mean excess value at chosen threshold

  • tmanual: logical; TRUE if the user passed a vector of thresholds

Details

The procedure consists in estimating the usual mean residual life as a function of the threshold, and looking for an order statistic or threshold value above which the fit is more or less linear.

References

Langousis, A., A. Mamalakis, M. Puliga and R. Deidda (2016). Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database, Water Resources Research, 52, 2659–2681.

Examples

thselect.mrl(rgp(n = 100))