Zobrazeno 1 - 10 of 94 pro vyhledávání: '"John H. J. Einmahl"'
1
Cube root weak convergence of empirical estimators of a density level set
Autor: Philippe Berthet, John H. J. Einmahl
Publikováno v: The Annals of Statistics
The Annals of Statistics, 2022, 50 (3), pp.1423-1446. ⟨10.1214/21-AOS2157⟩
The Annals of Statistics, 50(3), 1423-1446. Institute of Mathematical Statistics
Given n independent random vectors with common density f on R d , we study the weak convergence of three empirical-measure based estimators of the convex λ-level set L λ of f , namely the excess mass set, the minimum volume set and the maximum prob
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::517ef6f5dc69afab046c612a4a148992
https://arxiv.org/abs/2006.02229
Zobrazit plný text záznamu
2
Extreme Value Estimation for Heterogeneous Data
Autor: John H. J. Einmahl, Yi He
Publikováno v: Journal of Business & Economic Statistics, 41(1), 255-269. American Statistical Association
We develop a universal econometric formulation of empirical power laws possibly driven by parameter heterogeneity. Our approach extends classical extreme value theory to specifying the tail behavior of the empirical distribution of a general dataset
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e027ec979276c2bb6437c43cf2ec3176
https://doi.org/10.1080/07350015.2021.2008408
Zobrazit plný text záznamu
4
Empirical tail copulas for functional data
Autor: John H. J. Einmahl, Johan Segers
Publikováno v: Annals of Statistics, Vol. 49, no. 5, p. 2672-2696 (2021)
The Annals of Statistics, 49(5), 2672-2696. Institute of Mathematical Statistics
For multivariate distributions in the domain of attraction of a max-stable distribution, the tail copula and the stable tail dependence function are equivalent ways to capture the dependence in the upper tail. The empirical versions of these function
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4ad7bea516d3d4ec7da8dd35907e8a1
https://doi.org/10.1214/21-aos2050
Zobrazit plný text záznamu
5
Spatial dependence and space–time trend in extreme events
Autor: John H. J. Einmahl, Ana Ferreira, Laurens de Haan, Cláudia Neves, Chen Zhou
Publikováno v: The Annals of Statistics, 50(1), 30-52. Institute of Mathematical Statistics
Annals of Statistics, 50(1):50(1), 30-52. Institute of Mathematical Statistics
The statistical theory of extremes is extended to observations that are non-stationary and not independent. The non-stationarity over time and space is controlled via the scedasis (tail scale) in the marginal distributions. Spatial dependence stems f
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::225a99f8ccfc0220ef52fccc5647099b
https://doi.org/10.1214/21-aos2067
Zobrazit plný text záznamu
6
Testing the multivariate regular variation model
Autor: John H. J. Einmahl, Fan Yang, Chen Zhou
Publikováno v: Journal of Business & Economic Statistics, 39(4), 907-919. American Statistical Association
Journal of Business and Economic Statistics, 39(4), 907-919. Taylor & Francis Ltd
In this paper, we propose a test for the multivariate regular variation model. The test is based on testing whether the extreme value indices of the radial component conditional on the angular component falling in different subsets are the same. Comb
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c5f25aaf590ad723bf30b6170e8a8e6
https://research.tilburguniversity.edu/en/publications/084cc081-616a-4111-80ac-ebb96bef7083
Zobrazit plný text záznamu
7
Limits to Human Life Span Through Extreme Value Theory
Autor: Laurens de Haan, John H. J. Einmahl, Jesson Einmahl
Publikováno v: Journal of the American Statistical Association, 114(527), 1075-1080. Taylor and Francis Ltd.
There is no scientific consensus on the fundamental question whether the probability distribution of the human life span has a finite endpoint or not and, if so, whether this upper limit changes over time. Our study uses a unique dataset of the ages
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f70eb72495d41f3c07904a2b72bdad0f
https://doi.org/10.1080/01621459.2018.1537912
Zobrazit plný text záznamu
8
EXTREME VALUE STATISTICS IN SEMI-SUPERVISED MODELS
Autor: John H. J. Einmahl, Hanan Ahmed, Chen Zhou
Publikováno v: SSRN Electronic Journal.
We consider extreme value analysis in a semi-supervised setting, where we observe, next to the n data on the target variable, n +m data on one or more covariates. This is called the semi-supervised model with n labeled and m unlabeled data. By exploi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::39db87db8a135dca9a0972eacad3173e
https://doi.org/10.2139/ssrn.3795972
Zobrazit plný text záznamu
10
Two-Sample Testing for Tail Copulas with an Application to Equity Indices
Autor: John H. J. Einmahl, Sami Umut Can, Roger J. A. Laeven
Publikováno v: Journal of Business & Economic Statistics. American Statistical Association
A novel, general two-sample hypothesis testing procedure is established for testing the equality of tail copulas associated with bivariate data. More precisely, using an ingenious transformation of a natural two-sample tail copula process, a test pro
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e4fa415f490e6373df418bc946a39fb
https://doi.org/10.2139/ssrn.3880295
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje