Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Krajina, Andrea"'
Threshold selection plays a key role for various aspects of statistical inference of rare events. Most classical approaches tackling this problem for heavy-tailed distributions crucially depend on tuning parameters or critical values to be chosen by
Externí odkaz:
http://arxiv.org/abs/1903.02517
Autor:
Schmidt-Hieber, Johannes, Schneider, Laura Fee, Staudt, Thomas, Krajina, Andrea, Aspelmeier, Timo, Munk, Axel
Estimation of the population size $n$ from $k$ i.i.d.\ binomial observations with unknown success probability $p$ is relevant to a multitude of applications and has a long history. Without additional prior information this is a notoriously difficult
Externí odkaz:
http://arxiv.org/abs/1809.02443
Tail dependence models for distributions attracted to a max-stable law are fitted using observations above a high threshold. To cope with spatial, high-dimensional data, a rank-based M-estimator is proposed relying on bivariate margins only. A data-d
Externí odkaz:
http://arxiv.org/abs/1403.1975
Publikováno v:
Annals of Statistics 2012, Vol. 40, No. 3, 1764-1793
Consider a random sample in the max-domain of attraction of a multivariate extreme value distribution such that the dependence structure of the attractor belongs to a parametric model. A new estimator for the unknown parameter is defined as the value
Externí odkaz:
http://arxiv.org/abs/1112.0905
Publikováno v:
Bernoulli 2008, Vol. 14, No. 4, 1003-1026
In the world of multivariate extremes, estimation of the dependence structure still presents a challenge and an interesting problem. A procedure for the bivariate case is presented that opens the road to a similar way of handling the problem in a tru
Externí odkaz:
http://arxiv.org/abs/0710.2039
Autor:
Schneider, Laura Fee1 (AUTHOR) lfee.schneider@gmail.com, Krajina, Andrea1 (AUTHOR), Krivobokova, Tatyana2 (AUTHOR)
Publikováno v:
Extremes. Dec2021, Vol. 24 Issue 4, p881-913. 33p.
Publikováno v:
Journal of the Royal Statistical Society. Series B (Statistical Methodology), 2016 Jan 01. 78(1), 275-298.
Externí odkaz:
http://www.jstor.org/stable/24775337
Autor:
Einmahl, John, Krajina, Andrea
Multivariate regular variation is a common assumption in the statistics literature and needs to be verified in real-data applications. We develop a novel hypothesis test for multivariate regular variation, employing localized empirical likelihood. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::b926859b1eeacfee17e3c3e61a066503
https://research.tilburguniversity.edu/en/publications/261583f5-c571-48c6-8cea-945ba6542026
https://research.tilburguniversity.edu/en/publications/261583f5-c571-48c6-8cea-945ba6542026
Publikováno v:
The Annals of Statistics, 2012 Jun 01. 40(3), 1764-1793.
Externí odkaz:
https://www.jstor.org/stable/41713693
Publikováno v:
Bernoulli, 2008 Nov 01. 14(4), 1003-1026.
Externí odkaz:
https://www.jstor.org/stable/20680129