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pro vyhledávání: '"Betsch, Steffen"'
Autor:
Betsch, Steffen
Publikováno v:
Journal of Theoretical Probability, Volume 36, pages 2501-2563, (2023)
In the language of random counting measures many structural properties of the Poisson process can be studied in arbitrary measurable spaces. We provide a similarly general treatise of Gibbs processes. With the GNZ equations as a definition of these o
Externí odkaz:
http://arxiv.org/abs/2201.11415
Autor:
Betsch, Steffen, Last, Günter
Publikováno v:
Annales de l'Institut Henri Poincar\'e, Probabilit\'es et Statistiques, Volume 59, Issue 2, pages 706-725, (2023)
We prove that the distribution of a Gibbs process with non-negative pair potential is uniquely determined as soon as an associated Poisson-driven random connection model (RCM) does not percolate. Our proof combines disagreement coupling in continuum
Externí odkaz:
http://arxiv.org/abs/2108.06303
Publikováno v:
Electronic Journal of Statistics, Volume 16, Issue 1, pages 1303-1329, (2022)
From the distributional characterizations that lie at the heart of Stein's method we derive explicit formulae for the mass functions of discrete probability laws that identify those distributions. These identities are applied to develop tools for the
Externí odkaz:
http://arxiv.org/abs/2011.04369
Publikováno v:
The Canadian Journal of Statistics, Volume 49, Issue 2, pages 514-548, (2021)
We propose and investigate a new estimation method for the parameters of models consisting of smooth density functions on the positive half axis. The procedure is based on a recently introduced characterization result for the respective probability d
Externí odkaz:
http://arxiv.org/abs/1909.00002
Autor:
Betsch, Steffen, Ebner, Bruno
Publikováno v:
Annals of the Institute of Statistical Mathematics, Volume 73, Issue 1, pages 31-59, (2021)
By extrapolating the explicit formula of the zero-bias distribution occurring in the context of Stein's method, we construct characterization identities for a large class of absolutely continuous univariate distributions. Instead of trying to derive
Externí odkaz:
http://arxiv.org/abs/1810.06226
Autor:
Betsch, Steffen, Ebner, Bruno
Publikováno v:
Metrika, Volume 82, Issue 7, pages 779-806, (2019)
We propose a class of weighted $L_2$-type tests of fit to the Gamma distribution. Our novel procedure is based on a fixed point property of a new transformation connected to a Steinian characterization of the family of Gamma distributions. We derive
Externí odkaz:
http://arxiv.org/abs/1806.06028
Autor:
Betsch, Steffen, Ebner, Bruno
Publikováno v:
TEST, Volume 29, Issue 1, pages 105-138, (2020)
We propose two families of tests for the classical goodness-of-fit problem to univariate normality. The new procedures are based on $L^2$-distances of the empirical zero-bias transformation to the normal distribution or the empirical distribution of
Externí odkaz:
http://arxiv.org/abs/1803.07069
Akademický článek
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Akademický článek
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Autor:
Betsch, Steffen1 (AUTHOR) Steffen.Betsch@kit.edu, Ebner, Bruno1 (AUTHOR), Klar, Bernhard1 (AUTHOR)
Publikováno v:
Canadian Journal of Statistics. Jun2021, Vol. 49 Issue 2, p514-548. 35p.
