By a theorem due to Sklar, a multivariate distribution can be represented in terms of its underlying margins by binding them together using a copula function. By exploiting this representation, the “copula approach” to statistical modelling proceeds by specifying distributions for each margin and a copula function. In this paper, a number of families of copula functions are given, with attentio...

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. We derive the distribution of the copula value, which is particularly useful for tests and constructing ...

We propose a new test for the hypothesis that a bivariate copula is an Archimedean copula. The test statistic is based on a combination of two measures resulting from the characterization of Archimedean copulas by the property of associativity and by a strict upper bound on the diagonal by the Fréchet-upper bound. We prove weak convergence of this statistic and show that the critical values of ...

The copulas of random vectors with standard uniform univariate margins truncated from the right are considered and a general formula for such right-truncated conditional is derived. This analytical that can be inverted analytically as functions each single argument. case Archimedean related copulas. resulting not only tractable but also characterized tilted copulas, one main contributions this ...

We develop sampling algorithms for multivariate Archimedean copulas. For exchangeable copulas, where there is only one generating function, we first analyse the distribution of the copula itself, deriving a number of integral representations and a generating function representation. One of the integral representations is related, by a form of convolution, to the distribution whose Laplace trans...

Bivariate survival analysis has wide applications. In the presence of covariates, most literature focuses on studying their effects on the marginal distributions. However covariates can also affect the association between the two variables. In this article we consider the latter issue by proposing a nonstandard local linear estimator for the concordance probability as a function of covariates. ...

A symbolic variable is often described by a histogram. More generally, it can be provided in the form of a continuous distribution. In this case, the problem is to solve the most frequent problem in data mining, namely: to classify the objects starting from the description of the variables in the form of continuous distributions. A solution is to sample each distribution in a number N of points...

We examine the dependence structure of electricity spot prices across regional markets in the Australian National Electricity Market (NEM). Our analysis is based on a GARCH approach to model the marginal price series in the considered regions in combination with copulae to capture the dependence structure between the different markets. We apply different copula models including Archimedean, ell...

This paper develops a testing framework for comparing the predictive accuracy of competing multivariate density forecasts with different predictive copulas, focusing on specific parts of the copula support. The tests are framed in the context of the Kullback– Leibler Information Criterion, using (out-of-sample) conditional likelihood and censored likelihood in order to focus the evaluation on t...

Abstract Today Indonesia is experiencing health problems that are also being faced by all countries in the world, namely Covid-19. Jakarta, capital of state Indonesia, one provinces has been epicenter Covid-19 cases. Aim study to determine dependency between and maximum temperature Indonesia. Data cases used daily cumulative cases, new deaths. The correlations Pearson, Spearman, Kendall. correl...