Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

Archimedean copula estimation using Bayesian splines smoothing techniques

Copulas enable to specifymultivariate distributions with givenmarginals.Various parametric proposals weremade in the literature for these quantities, mainly in the bivariate case. They can be systematically derived from multivariate distributions with known marginals, yielding e.g. the normal and the Student copulas. Alternatively, one can restrict his/her interest to a sub-family of copulas na...

Copula-Based Quantile Autoregression

Parametric copulae are shown to be an attractive device for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed estimators are established, leading to a general framework for inference and model specificat...

Copula-based nonlinear quantile autoregression

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed quantile estimators are established under mild conditions, allowing fo...

Goodness-of-fit Tests for Archimedean Copula Models

In this paper, we propose two tests for parametric models belonging to the Archimedean copula family, one for uncensored bivariate data and the other one for right-censored bivariate data. Our test procedures are based on the Fisher transform of the correlation coefficient of a bivariate (U, V ), which is a one-toone transform of the original random pair (T1, T2) that can be modeled by an Archi...

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