Results 91 to 100 of about 153,166 (217)

Local dependence in bivariate copulae with Beta marginals

Revista Colombiana de Estadística, 2017
The local dependence function (LDF) describes changes in the correlation structure of continuous bivariate random variables along their range. Bivariate density functions with Beta marginals can be used to model jointly a wide variety of data with bounded outcomes in the (0,1) range, e.g. proportions.
Eirini Koutoumanou, Angie Wade, Mario Cortina-Borja   +2 more
openaire   +6 more sources

A class of bivariate copula mappings

, 2021
Šioje disertacijoje nagrinėjame vieną dvimačių kopulų atvaizdį, kuris leidžia lengvai konstruoti naujas kopulas ir kopulų šeimas. Darbe pateikiame būtinas ir pakankamas sąlygas vienmatei funkcijai, su kuria atvaizdžio rezultatas yra kopula bet kuriai dvimatei kopulai. Tada nagrinėjame minėto atvaizdžio savybes.
openaire   +2 more sources

Vine copulas structures modeling on Russian stock market

Discrete and Continuous Models and Applied Computational Science, 2019
Pair-copula constructions have proven to be a useful tool in statistical modeling, particularly in the field of finance. The copula-based approach can be used to choose a model that describes the dependence structure and marginal behaviour of the data in
Eugeny Yu. Shchetinin
doaj   +1 more source

Efficient correlation matching for fitting discrete multivariate distributions with arbitrary marginals and normal-copula dependence [PDF]

, 2009
A popular approach for modeling dependence in a finite-dimensional random vector X with given univariate marginals is via a normal copula that fits the rank or linear correlations for the bivariate marginals of X.
Avramidis, Athanassios N., L'Ecuyer, Pierre, Channouf, Nabil, Pierre L'Ecuyer, Nabil Channouf, Athanassios N. Avramidis   +5 more
core   +1 more source

Construction of copulas for bivariate failure rates

Annals of Operations Research
AbstractThis paper aims to develop a method to construct an asymmetric copula, based on which a closed form of the cumulative bivariate failure rate can be obtained. The construction method differs from existing ones. This new method can facilitate the derivation of some results such as the estimation of the expected number of occurrences for a system ...
Shaomin Wu, Hongyan Dui, Linmin Hu
openaire   +2 more sources

A copula-based bivariate integer-valued autoregressive process with application

Modern Stochastics: Theory and Applications, 2019
A bivariate integer-valued autoregressive process of order 1 (BINAR(1)) with copula-joint innovations is studied. Different parameter estimation methods are analyzed and compared via Monte Carlo simulations with emphasis on estimation of the copula ...
Andrius Buteikis, Remigijus Leipus
doaj   +1 more source

Bivariate measure-inducing quasi-copulas

Fuzzy Sets and Systems
It is well known that every bivariate copula induces a positive measure on the Borel $σ$-algebra on $[0,1]^2$, but there exist bivariate quasi-copulas that do not induce a signed measure on the same $σ$-algebra. In this paper we show that a signed measure induced by a bivariate quasi-copula can always be expressed as an infinite combination of measures
openaire   +4 more sources

Modelling cascading effects for systemic risk: Properties of the Freund copula

Dependence Modeling, 2019
We consider a dependent lifetime model for systemic risk, whose basic idea was for the first time presented by Freund. This model allows to model cascading effects of defaults for arbitrarily many economic agents.
Guzmics Sándor, Pflug Georg Ch.
doaj   +1 more source

Improving Upon the Marginal Empirical Distribution Functions when the Copula is Known [PDF]

At the heart of the copula methodology in statistics is the idea of separating marginal distributions from the dependence structure. However, as shown in this paper, this separation is not to be taken for granted: in the model where the copula is known ...
Werker, B.J.M., Akker, R. van den, Segers, J.J.J.   +2 more
core  

Bivariate Cox model and copulas

, 2009
This paper introduces a new class of Cox models for dependent bivariate data. The impact of the covariate on the dependence of the variables is captured through the modification of their copula. Various classes of well known copulas are stable under the model (archimedean type and extreme value copulas), meaning that the role of the covariate acts in a
Achibi, Mohamed, Broniatowski, Michel
openaire   +3 more sources