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References in periodicals archive ?
The "Penalized Maximum Likelihood Estimator and Risk Measure Estimators" section then presents the details about the fitting procedure.
In this section, we present the penalized maximum likelihood estimator and a backfitting algorithm for simultaneously estimating the parameters [xi] and v (thus [beta]) associated with the approximate GPD for the excesses; see (9) and (10) above.
The simulated losses are drawn from a (nonstationary) GPD depending on the covariates "year" and "group." We remove the losses of year 2006 in group "A" (to mimic having no losses for this yeargroup combination) and then fit the (Poisson process) intensity A and the two GPD parameters [xi] and [beta] depending on "year" and "group" and compute bootstrapped confidence intervals using the methodology presented in the "Loss Frequency" section to "The Penalized Maximum Likelihood Estimator and Risk Measure Estimators" section.