Results 11 to 20 of about 493 (183)

Permutation Tests Based on the Copula-Graphic Estimator and Their Use for Survival Tree Construction. [PDF]

open access: yesStat Med
ABSTRACT Survival trees are popular alternatives to Cox or Aalen regression models that offer both modeling flexibility and graphical interpretability. This paper introduces a new algorithm for survival trees that relaxes the assumption of independent censoring. To this end, we use the copula‐graphic estimator to estimate survival functions.
Baur P, Pauly M, Emura T.
europepmc   +2 more sources

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

open access: yesStat Med
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.
Sun J, Cook T.
europepmc   +2 more sources

Convergence of Archimedean copulas [PDF]

open access: yesStatistics & Probability Letters, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Charpentier, Arthur, Segers, Johan
openaire   +5 more sources

Compound Archimedean Copulas

open access: yesInternational Journal of Statistics and Probability, 2021
The copula function is an effective and elegant tool useful for modeling dependence between random variables. Among the many families of this function, one of the most prominent family of copula is the Archimedean family, which has its unique structure and features.
Moshe Kelner   +2 more
openaire   +2 more sources

Time Varying Hierarchical Archimedean Copulae [PDF]

open access: yesSSRN Electronic Journal, 2010
There is increasing demand for models of time-varying and non-Gaussian dependencies for multivariate time-series. Available models suffer from the curse of dimensionality or restrictive assumptions on the parameters and the distribution. A promising class of models are the hierarchical Archimedean copulae (HAC) that allow for non-exchangeable and non ...
Wolfgang Karl Härdle   +2 more
openaire   +2 more sources

Local Dependence for Bivariate Weibull Distributions Created by Archimedean Copula

open access: yesمجلة بغداد للعلوم, 2021
In multivariate survival analysis, estimating the multivariate distribution functions and then measuring the association between survival times are of great interest.
Swar O. Ahmed   +2 more
doaj   +1 more source

Generative Archimedean Copulas

open access: yes, 2021
We propose a new generative modeling technique for learning multidimensional cumulative distribution functions (CDFs) in the form of copulas. Specifically, we consider certain classes of copulas known as Archimedean and hierarchical Archimedean copulas, popular for their parsimonious representation and ability to model different tail dependencies.
Ng, Yuting   +3 more
openaire   +2 more sources

The Copula Derived from the SAHARA Utility Function

open access: yesRisks, 2022
A new Archimedean copula family is presented that was derived from the SAHARA utility function introduced in the economic literature in 2011. Its properties are discussed, and its flexibility and versatility are demonstrated.
Jaap Spreeuw
doaj   +1 more source

Using Copulas to Model Dependence Between Crude Oil Prices of West Texas Intermediate and Brent-Europe [PDF]

open access: yesSahand Communications in Mathematical Analysis, 2020
In this study the main endeavor is to model dependence structure  between crude oil prices of West Texas Intermediate (WTI) and Brent - Europe.  The main activity is on concentrating copula technique which is powerful technique in modeling dependence ...
Vadoud Najjari
doaj   +1 more source

Properties of hierarchical Archimedean copulas [PDF]

open access: yesStatistics & Risk Modeling, 2013
Abstract In this paper we analyse the properties of hierarchical Archimedean copulas. This class is a generalisation of the Archimedean copulas and allows for general non-exchangeable dependency structures. We show that the structure of the copula can be uniquely recovered from all bivariate margins.
Ostap Okhrin   +2 more
openaire   +4 more sources

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