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Although the fundamental probabilistic theory of extremes has been welldeveloped, there are many practical considerations that must be addressed inapplication. The contribution of this thesis is four-fold. The first concernsthe choice of r in the r largest order statistics modeling of extremes. Thesecond contribution pertains to threshold selection in the peaks-over-thresholdapproach. The third combines a theoretical and methodological approach toimprove estimation within non-stationary regional frequency models of extremaldata  The methodology developed is demonstrated with climate based applications.Last, an overview of computational issues for extremes is provided, along witha brief tutorial of the R package eva, which improves the functionality ofexisting extreme value software, as well as providing new implementations.

Automated, Efficient, and Practical Extreme Value Analysis with Environmental Applications