On Nonparametric Measures of Dependence for Random Variables

Schweizer, B.; Wolff, Edward F.

doi:10.1214/aos/1176345528

Cited by 501 publications

(275 citation statements)

References 8 publications

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“…The concordance is one of these scale-invariant dependence forms. On the other hand, it is also known (cf., e.g., Schweizer and Wolf (1981)) that the copula functions capture the properties of dependence between random variables. A known statistical test of independence (Genest and Favre, 2007), for l¼2, is based on the empirical version of Kendall's t measure, that can be defined by…”

Section: Methodsmentioning

confidence: 99%

A dependence modelling study of extreme rainfall in Madeira Island

Gouveia-Reis

Lopes

Mendonça

2016

Physics and Chemistry of the Earth, Parts A/B/C

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a b s t r a c tThe dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

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Section: Methodsmentioning

confidence: 99%

A dependence modelling study of extreme rainfall in Madeira Island

Gouveia-Reis

Lopes

Mendonça

2016

Physics and Chemistry of the Earth, Parts A/B/C

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“…In this context, the residual series , i t  for i=1,2 as in Equation (2)  is given by Schweizer and Wolff (1981) in terms of copula as…”

Section:  mentioning

confidence: 99%

Measuring and Testing Tail Dependence and Contagion Risk Between Major Stock Markets

2016

Comput Econ

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In this paper, three copula GARCH models i.e. Gaussian, Student-t, and Clayton are used to estimate and test the tail dependence measured by Kendall's tau between six stock indices.Since the contagion risk spreads from large markets to small markets, the tail dependence is studied for smaller Taiwanese and South Korean stock markets, i.e. Taiex and Kospi against four larger stock markets, i.e. S&P500, Nikkei, MSCI China, and MSCI Europe. The vector autoregression result indicates that S&P500 and MSCI China indeed impact mostly and significantly to the other four stock markets. However, the tail dependence of both Taiex and Kospi against S&P500 and MSCI Chia are lower due to unilateral impacts from US and China.Using Clayton copula GARCH, the threshold tests of Kendall's tau between most stock markets except China are significant during both subprime and Greek debt crises. The tests of Studentt copula GARCH estimated Kendall's taus are only acceptable for subprime crisis but not for Greek debt crisis. Thus, Clayton copula GARCH is found appropriate to estimate Kendall's taus as tested by threshold regression.

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“…The marginal distributions of T 1 and T 2 do not a ect (11), and hence it follows that only depends on the copula function C T1T2 [27]. Kendall's thus measures the association between both time points after adjustment for the covariates used in the model.…”

Section: Kendall'smentioning

confidence: 99%

Pseudo‐likelihood estimation for a marginal multivariate survival model

Tibaldi

Molenberghs

Burzykowski

et al. 2004

Statistics in Medicine

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SUMMARYIn this paper, we propose a multivariate Plackett-Dale model for survival outcomes. A pseudo-likelihood method for the estimation of the parameters is proposed and these ideas are applied to two case studies. The modelling approach is similar in spirit but di erent from Parner's approach. The ÿrst study is in AIDS, where the overall survival time and di erent opportunistic infections in HIV-infected patients are studied. The second study is on adoption data where the association of the survival times within families is modelled, illustrating the use of the proposed methodology for the context of population genetics.

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On Nonparametric Measures of Dependence for Random Variables

Cited by 501 publications

References 8 publications

A dependence modelling study of extreme rainfall in Madeira Island

A dependence modelling study of extreme rainfall in Madeira Island

Measuring and Testing Tail Dependence and Contagion Risk Between Major Stock Markets

Pseudo‐likelihood estimation for a marginal multivariate survival model

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