To promote the development level of urban sustainability, more and cities have been paying attention to improvement public transportation. City managers intend attract people from private cars transport by improving service transport. The operational reliability bus lines plays a crucial role in maintaining high-level Previous studies focused on whole line investigating overall stability depart...

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality. In this paper, for non-elliptically distributed financial returns, we propose copula-based multivariate GARCH (C-MGARCH) model with uncorrelated dependent errors, which are generated through a linear combination of dependent random variables. The dependence structure is controlled by a copula function. Our ne...

Consider the model Y = m(X)+ ε, where m(·) = med(Y |·) is unknown but smooth. It is often assumed that ε and X are independent. However, in practice this assumption is in many cases violated. In this paper we propose to model the dependence between ε and X by means of a copula model, i.e. (ε,X) ∼ Cθ(Fε(·), FX(·)), where Cθ is a copula function depending on an unknown parameter θ, and Fε and FX ...

The catastrophic nature of seismic risk is attributed to spatiotemporal correlation of seismic losses of buildings and infrastructure. For seismic risk management, such correlated seismic effects must be adequately taken into account, since they affect the probability distribution of aggregate seismic losses of spatially distributed structures significantly, and its upper tail behavior can be o...

Entropy is a measure of uncertainty and has been commonly used for various applications, including probability inferences in hydrology. Copula has been widely used for constructing joint distributions to model the dependence structure of multivariate hydrological random variables. Integration of entropy and copula theories provides new insights in hydrologic modeling and analysis, for which the...

In this paper, we are proposing a flexible method for constructing bivariate generalized Farlie-Gumbel-Morgenstern (G-FGM) copula family. The is mainly developed around the function $\phi(t)$ ($t\in [0,1]$), where $\phi$ generator of G-FGM copula. proposed construction has useful advantages. first which direct relationship between and Kendall's tau. second advantage possibility multi-parameter ...

We show that all multivariate Extreme Value distributions, which are the possible weak limits of the K largest order statistics of iid sequences, have the same copula, the so called K-extremal copula. This copula is described through exact expressions for its density and distribution functions. We also study measures of dependence, we obtain a weak convergence result and we propose a simulation...

Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of vine tree structure, copula families for each pair copula term and their corresponding parameters. In this survey we discuss the different approaches, both frequentist as...

The paper presents an overview of financial applications of copulas. Copulas permit to represent joint distribution functions by splitting the marginal behavior, embedded in the marginal distributions, from the dependence, captured by the copula itself. The splitting proves to be very helpful not only in the modelling phase, but also in the estimation or simulation one. Essentially, it provides...

In information theory, mutual information (MI) is a difference concept with entropy.[1] In this paper, we prove with copula [2] that they are essentially same – mutual information is also a kind of entropy, called copula entropy. Based on this insightful result, We propose a simple method for estimating mutual information. Copula is a theory on dependence and measurement of association.[2] Skla...