Functions for Extreme Value Mixture Modelling, Threshold Estimation and Boundary Corrected Kernel Density Estimation
The usual distribution functions, maximum likelihood inference and model diagnostics for univariate stationary extreme value mixture models are provided.
Kernel density estimation including various boundary corrected kernel density estimation methods and a wide choice of kernels, with cross-validation likelihood based bandwidth estimators are included.
Reasonable consistency with the base functions in the
evd package is
provided, so that users can safely interchange most code.
Carl Scarrott and Yang Hu, University of Canterbury, New Zealand firstname.lastname@example.org
Scarrott, C.J. and MacDonald, A. (2012). A review of extreme value threshold estimation and uncertainty quantification. REVSTAT - Statistical Journal 10(1), 33-59. Available from http://www.ine.pt/revstat/pdf/rs120102.pdf
Hu, Y. (2013). Extreme value mixture modelling: An R package and simulation study. MSc (Hons) thesis, University of Canterbury, New Zealand. http://ir.canterbury.ac.nz/simple-search?query=extreme&submit=Go
MacDonald, A. (2012). Extreme value mixture modelling with medical and industrial applications. PhD thesis, University of Canterbury, New Zealand. http://ir.canterbury.ac.nz/bitstream/10092/6679/1/thesis_fulltext.pdf