Strong approximation for the deviation of kernel copula estimators
  We prove a uniform in bandwidth law of the iterated logarithm for the maximal deviation of kernel copula estimators from their expectations. We deal especially with the \textit{local linear}, the \textit{mirror-reflection} and the \textit{transformation} estimators. These results are useful for establishing the strong uniform in bandwidth consistency of these kernel estimators. 
Diam Ba, Seck Cheikh Tidiane, Lo Gane Samb
stat.ME