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This article proposes a space-efficient approximation to empirical taildependence coefficients of an indefinite bivariate stream of data. Theapproximation, which has stream-length invariant error bounds, utilises recentwork on the development of a summary for bivariate empirical copula functions.The work in this paper accurately approximates a bivariate empirical copula inthe tails of each marginal distribution, therefore modelling the taildependence between the two variables observed in the data stream. Copulasevaluated at these marginal tails can be used to estimate the tail dependencecoefficients. Modifications to the space-efficient bivariate copulaapproximation, presented in this paper, allow the error of approximations tothe tail dependence coefficients to remain stream-length invariant. Theoreticaland numerical evidence of this, including a case-study using the Los AlamosNational Laboratory netflow data-set, is provided within this article.

Space-efficient estimation of empirical tail dependence coefficients for bivariate data streams