Results 11 to 20 of about 165,609 (118)

Causal Inference for First Non‐Fatal Events With the Competing Risk of Death: A Principal Stratification Approach [PDF]

Statistics in Medicine, Volume 44, Issue 25-27, November 2025.
ABSTRACT In clinical trials involving both mortality and morbidity, an active treatment can influence the observed risk of the first nonfatal event either directly, through its effect on the underlying nonfatal event process, or indirectly, through its effect on the death process, or both.
Jiren Sun, Thomas Cook
wiley   +2 more sources

Nested Archimedean Copulas MeetR: ThenacopulaPackage [PDF]

Journal of Statistical Software, 2011
The package nacopula provides procedures for constructing nested Archimedean copulas in any dimensions and with any kind of nesting structure, generating vectors of random variates from the constructed objects, computing function values and probabilities of falling into hypercubes, as well as evaluation of characteristics such as Kendall's tau and ...
Hofert, Marius, Mächler, Martin; id_orcid0000-0002-8685-9910   +1 more
openaire   +4 more sources

Sampling nested Archimedean copulas with applications to CDO pricing

, 2010
Copulas are distribution functions with standard uniform univariate margins. One particular parametric class of copulas is the class Archimedean copulas. These copulas are explicit and can be expressed in terms of a one-dimensional function called the generator of the Archimedean copula. Archimedean copulas are permutation symmetric in their arguments.
Hofert, Marius
openaire   +3 more sources

Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on Copula functions [PDF]

Natural Hazards and Earth System Sciences, 2012
This paper presents an advanced approach to statistically analyse storm surge events. In former studies the highest water level during a storm surge event usually was the only parameter that was used for the statistical assessment.
T. Wahl, C. Mudersbach, J. Jensen
doaj   +1 more source

Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises

Journal of Forecasting, Volume 42, Issue 8, Page 2139-2166, December 2023., 2023
Abstract We employ and examine vine copulas in modeling symmetric and asymmetric dependency structures and forecasting financial returns from 2001 to 2022, a period that includes the 2008 financial crisis, the 2011 European sovereign debt crisis, the 2020 COVID‐19 pandemic crisis, and the 2022 Russian invasion of Ukraine with the resulting energy ...
Maziar Sahamkhadam, Andreas Stephan
wiley   +1 more source

Matrix-Tilted Archimedean Copulas [PDF]

, 2021
The new class of matrix-tilted Archimedean copulas is introduced. It combines properties of Archimedean and elliptical copulas by introducing a tilting matrix in the stochastic representation of Archimedean copulas, similar to the Cholesky factor for ...
Marius Hofert, Hofert, Marius, Ziegel, Johanna F., Johanna F. Ziegel   +3 more
core   +2 more sources

Nonparametric estimation of the tree structure of a nested Archimedean copula [PDF]

Computational Statistics & Data Analysis, 2014
25 pages, 9 ...
Johan Segers, Nathan Uyttendaele
openaire   +2 more sources

D‐vine‐copula‐based postprocessing of wind speed ensemble forecasts

Quarterly Journal of the Royal Meteorological Society, Volume 149, Issue 755, Page 2575-2597, July 2023 Part B., 2023
In the global postprocessing of wind speed ensemble forecasts, the D‐vine copula quantile regression (DVQR) is able to substantially outperform the boosted zero‐truncated ensemble model output statistics with gradient‐boosting extensions (tEMOS‐GB) with respect to the continuous ranked probability skill score (CRPSS), as shown in the figure.
David Jobst, Annette Möller, Jürgen Groß   +2 more
wiley   +1 more source

Smooth copula‐based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada

Environmetrics, Volume 34, Issue 3, May 2023., 2023
Abstract This paper proposes a smooth copula‐based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in Central Eastern Canada. The considered data contains a large portion of missing values, and one observes several nonconcomitant record periods at different stations.
Fatima Palacios‐Rodriguez, Elena Di Bernardino, Melina Mailhot   +2 more
wiley   +1 more source

Stochastic fundamental diagram modeling using asymmetric vine and nested Archimedean copulas

Transportation Research Part B: Methodological
Qixiu Cheng, Yuming Zhou
exaly   +2 more sources