Results 21 to 30 of about 70,213 (199)

Financial dependence analysis: applications of vine copulas [PDF]

Statistica Neerlandica, 2013
This paper features the application of a novel and recently developed method of statistical and mathematical analysis to the assessment of financial risk, namely regular vine copulas. Dependence modelling using copulas is a popular tool in financial applications but is usually applied to pairs of securities.
Allen, David E., Ashraf, Mohammad.A., McAleer, Michael, Powell, Robert J., Singh, Abhay K.   +4 more
openaire   +8 more sources

Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine [PDF]

Journal of Statistical Software, 2013
Flexible multivariate distributions are needed in many areas. The popular multivariate Gaussian distribution is however very restrictive and cannot account for features like asymmetry and heavy tails.
Eike Christian Brechmann, Ulf Schepsmeier   +1 more
doaj   +2 more sources

Model selection tests for truncated vine copulas under nested hypotheses

Dependence Modeling
Vine copulas, constructed using bivariate copulas as building blocks, provide a flexible framework for modeling multi-dimensional dependencies.
Nishi Ichiro, Kawasaki Yoshinori
doaj   +2 more sources

Application of vine copulas to dependence analysis of water quality data [PDF]

Journal of Applied Research in Water and Wastewater, 2022
In this study, using vine copulas and tree sequences, dependence analysis of groundwater quality variables (Total hardness (TH), Sodium adsorption ratio (SAR), Sodium percentage (Na %) and magnesium (Mg)) was performed.
Mohammad Nazeri Tahroudi, Yousef Ramezani, Carlo De Michele, Rasoul Mirabbasi   +3 more
doaj   +1 more source

Textile effluent treatment using Avocado seeds based activated carbon [PDF]

Journal of Applied Research in Water and Wastewater, 2022
In this study, using vine copulas and tree sequences, dependence analysis of groundwater quality variables (Total hardness (TH), Sodium adsorption ratio (SAR), Sodium percentage (Na %) and magnesium (Mg)) was performed.
Jacques Munyegaju, Hakizimana Jean Nepo, Buscotin Beakou, Valerien Mutambyi, Uwitonze Nestor   +4 more
doaj   +1 more source

Copulas for Covariate Simulation in Pharmacometrics. [PDF]

CPT Pharmacometrics Syst Pharmacol
ABSTRACT Patient‐specific covariates are commonly incorporated in pharmacometric and quantitative system pharmacology models to predict differences in pharmacokinetic or pharmacodynamic profiles between patients. When simulating new virtual populations of patients, generating realistic covariate sets that accurately reflect the correlation structures ...
Guo Y, Guo T, van Hasselt JGC, Zwep LB.
europepmc   +2 more sources

Streamflow estimation at partially gaged sites using multiple-dependence conditions via vine copulas [PDF]

Hydrology and Earth System Sciences, 2021
Reliable estimates of missing streamflow values are relevant for water resource planning and management. This study proposes a multiple-dependence condition model via vine copulas for the purpose of estimating streamflow at partially gaged sites.
K.-H. Ahn
doaj   +1 more source

Vine constructions of Lévy copulas [PDF]

Journal of Multivariate Analysis, 2013
Levy copulas are the most general concept to capture jump dependence in multivariate Levy processes. They translate the intuition and many features of the copula concept into a time series setting. A challenge faced by both, distributional and Levy copulas, is to find flexible but still applicable models for higher dimensions. To overcome this problem,
Grothe, Oliver, Nicklas, Stephan
openaire   +3 more sources

Smooth nonparametric Bernstein vine copulas [PDF]

Quantitative Finance, 2012
We propose to use nonparametric Bernstein copulas as bivariate pair-copulas in high-dimensional vine models. The resulting smooth and nonparametric vine copulas completely obviate the error-prone need for choosing the pair-copulas from parametric copula families. By means of a simulation study and an empirical analysis of financial market data, we show
Weiß, Gregor, Scheffer, Marcus
openaire   +2 more sources

Approximate Uncertainty Modeling in Risk Analysis with Vine Copulas. [PDF]

Risk Anal, 2016
Many applications of risk analysis require us to jointly model multiple uncertain quantities. Bayesian networks and copulas are two common approaches to modeling joint uncertainties with probability distributions. This article focuses on new methodologies for copulas by developing work of Cooke, Bedford, Kurowica, and others on vines as a way of ...
Bedford T, Daneshkhah A, Wilson KJ.
europepmc   +6 more sources