The efficiency of regional frequency analysis (RFA) is undermined by intersite dependence, which is usually ignored in parameter estimation. We propose a spatial index flood model where marginal generalized extreme value distributions are joined by an extreme-value copula characterized by a max-stable process for the spatial dependence. The parameters are estimated with a pairwise likelihood co...

A weighted empirical likelihood approach is proposed to take account of the heteroscedastic structure of the data. The resulting weighted empirical likelihood ratio statistic is shown to have a limiting chisquare distribution. A limited simulation study shows that the associated con*dence intervals for a population mean or a regression coe+cient have more accurate coverage probabilities and mor...

Accurate estimation of evolutionary distances between taxa is important for many phylogenetic reconstruction methods. Distances can be estimated using a range of different evolutionary models, from single nucleotide polymorphisms to large-scale genome rearrangements. Corresponding corrections for genome rearrangement distances fall into 3 categories: Empirical computational studies, Bayesian/MC...

In this paper, we will discuss the concept of almost sure convergence for specic groups of fuzzyrandom variables. For this purpose, we use the type of generalized Chebyshev inequalities.Moreover, we show the concept of almost sure convergence of weighted average pairwise NQDof fuzzy random variables.

In many of the possible applications as well as the theoretical models of computational social choice, the agents’ preferences are represented as partial orders. In this paper, we extend the maximum likelihood approach for defining “optimal” voting rules to this setting. We consider distributions in which the pairwise comparisons/incomparabilities between alternatives are drawn i.i.d. We call s...

This paper presents an interactive image segmentation approach where the segmentation problem is formulated as a probabilistic estimation manner. Instead of measuring the distances between unseeded pixels and seeded pixels, we measure the similarities between pixel pairs and seed pairs to improve the robustness to the seeds. The unary prior probability of each pixel belonging to the foreground ...