An estimator of the stable tail dependence function based on the empirical beta copula
The replacement of indicator functions by integrated beta kernels in the definition of the empirical tail dependence function is shown to produce a smoothed version of the latter estimator with the same asymptotic distribution but superior finite-sample performance. The link of the new estimator with the empirical beta copula enables a simple but effective resampling scheme.
|Bernstein polynomial, Bootstrap, Brown–Resnick process, Copula, Empirical process, Max-linear model, Tail copula, Tail dependence, Weak convergence|
|Extremes: statistical theory and applications in science, engineering and economics|
|Organisation||Department of Econometrics|
Kiriliouk, A.A, Segers, J. (Johan), & Tafakori, L. (Laleh). (2018). An estimator of the stable tail dependence function based on the empirical beta copula. Extremes: statistical theory and applications in science, engineering and economics, 1–20. doi:10.1007/s10687-018-0315-y