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pro vyhledávání: '"Ziegel, Johanna F."'
Forecasting and forecast evaluation are inherently sequential tasks. Predictions are often issued on a regular basis, such as every hour, day, or month, and their quality is monitored continuously. However, the classical statistical tools for forecas
Externí odkaz:
http://arxiv.org/abs/2109.11761
Autor:
Mühlemann, Anja, Ziegel, Johanna F.
We study the non-parametric isotonic regression problem for bivariate elicitable functionals that are given as an elicitable univariate functional and its Bayes risk. Prominent examples for functionals of this type are (mean, variance) and (Value-at-
Externí odkaz:
http://arxiv.org/abs/2106.15369
Autor:
Henzi, Alexander, Ziegel, Johanna F.
Probability forecasts for binary events play a central role in many applications. Their quality is commonly assessed with proper scoring rules, which assign forecasts a numerical score such that a correct forecast achieves a minimal expected score. I
Externí odkaz:
http://arxiv.org/abs/2103.08402
A Distributional (Single) Index Model (DIM) is a semi-parametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method is a combination of classical single index models for the estimation o
Externí odkaz:
http://arxiv.org/abs/2006.09219
Isotonic distributional regression (IDR) is a powerful nonparametric technique for the estimation of conditional distributions under order restrictions. In a nutshell, IDR learns conditional distributions that are calibrated, and simultaneously optim
Externí odkaz:
http://arxiv.org/abs/1909.03725
In general, the solution to a regression problem is the minimizer of a given loss criterion, and depends on the specified loss function. The nonparametric isotonic regression problem is special, in that optimal solutions can be found by solely specif
Externí odkaz:
http://arxiv.org/abs/1904.04761
This paper provides a characterization of all possible dependency structures between two stochastically ordered random variables. The answer is given in terms of copulas that are compatible with the stochastic order and the marginal distributions. Th
Externí odkaz:
http://arxiv.org/abs/1902.04299
Autor:
Fissler, Tobias, Ziegel, Johanna F.
Publikováno v:
Statistics & Risk Modeling, vol. 38, no. 1-2, 2021, pp. 25-46
The debate of what quantitative risk measure to choose in practice has mainly focused on the dichotomy between Value at Risk (VaR) -- a quantile -- and Expected Shortfall (ES) -- a tail expectation. Range Value at Risk (RVaR) is a natural interpolati
Externí odkaz:
http://arxiv.org/abs/1902.04489
Autor:
Fissler, Tobias, Ziegel, Johanna F.
Publikováno v:
Ann. Statist., Volume 49, Number 1 (2021), 614
This note corrects conditions in Proposition 3.4 and Theorem 5.2(ii) and comments on imprecisions in Propositions 4.2 and 4.4 in Fissler and Ziegel (2016).
Comment: 12 pages, 1 figure, to appear as a supplement in the Annals of Statistics
Comment: 12 pages, 1 figure, to appear as a supplement in the Annals of Statistics
Externí odkaz:
http://arxiv.org/abs/1901.08826
We analyze four different approaches to estimate a multivariate probability density (or the log-density) and its first and second order derivatives. Two methods, local log-likelihood and local Hyv\"arinen score estimation, are in terms of weighted sc
Externí odkaz:
http://arxiv.org/abs/1812.09322