Results 101 to 110 of about 70,213 (199)

A Bayesian Multi-Model Inference Method for Reliability Analysis Considering Vine Structure Uncertainty Under Limited Data

Applied Sciences
This paper investigates the epistemic uncertainty associated with dependence modeling and its impact on structural reliability analysis when data for vine structure selection is limited.
Qiang Li, Gang Li, Yan Zeng, Wanxin He
doaj   +1 more source

Non-linear optimal multivariate spatial design using spatial vine copulas [PDF]

, 2017
A multivariate spatial sampling design that uses spatial vine copulas is presented that aims to simultaneously reduce the prediction uncertainty of multiple variables by selecting additional sampling locations based on the multivariate relationship ...
Thompson, M. Helen, Musafer, G. Nishani
core   +2 more sources

Learning Vine Copula Models for Synthetic Data Generation

Proceedings of the AAAI Conference on Artificial Intelligence, 2019
A vine copula model is a flexible high-dimensional dependence model which uses only bivariate building blocks. However, the number of possible configurations of a vine copula grows exponentially as the number of variables increases, making model selection a major challenge in development.
Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni   +2 more
openaire   +4 more sources

Assessing Efficiency of D-Vine Copula ARMA-GARCH Method in Value at Risk Forecasting: Evidence from PSE Listed Companies

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2015
The article points out the possibilities of using static D-Vine copula ARMA-GARCH model for estimation of 1 day ahead market Value at Risk. For the illustration we use data of the four companies listed on Prague Stock Exchange in range from 2010 to 2014.
Václav Klepáč, David Hampel
doaj   +1 more source

Modelldistanzen, Block Maxima und wiederholte Messungen im Kontext von Vine Copulas

, 2017
This dissertation presents three novel aspects of vine copulas. The first part develops model distances based on the Kullback-Leibler distance that can be used for vine copulas even in high dimensions. The second part provides an explicit formula for the
Killiches, Matthias Markus
core  

Construction of asymmetric copulas and its application in two-dimensional reliability modelling [PDF]

, 2014
Copulas offer a useful tool in modelling the dependence among random variables. In the literature, most of the existing copulas are symmetric while data collected from the real world may exhibit asymmetric nature.
Wu, Shaomin
core   +1 more source

Gluing copulas [PDF]

We present a new way of constructing bivariate copulas, by recalling and gluing two (or more) copulas. Examples illustrate how this construction can be applied to build complicated copulas from simple ones. --
Siburg, Karl Friedrich, Stoimenov, Pavel A.   +1 more
core  

An econometric Study for Vine Copulas [PDF]

We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables.
Dominique Guegan, Pierre-André Maugis
core  

Value-at-Risk with Vine Copulas

, 2023
Especially when considering a portfolio with multiple assets the dependence structure in-between them is crucial regarding the grade of diversification and risk assessment. Models which consist of the multivariate normal distribution are popular because of their simplicity and fast calculation time.
openaire   +1 more source

Estimating Non-Simplified Vine Copulas Using Penalized Splines

, 2017
Schellhase C, Spanhel F. Estimating Non-Simplified Vine Copulas Using Penalized Splines. Statistics and Computing.
Schellhase, Christian ; https://orcid.org/, Spanhel, Fabian, Christian Schellhase, Fabian Spanhel   +3 more
core   +1 more source