The blockwise bootstrap for general empirical processes of stationary sequences

We apply the blockwise bootstrap for stationary observations, proposed by Künsch (1989), to empirical processes indexed by function classes which satisfy some bracketing conditions. We prove a bootstrap central limit theorem for empirical processes of stationary [beta]-mixing variables, which holds almost surely. This is done under a moment condition for the envelope function of and by assuming an exponential decay of the mixing coefficients. By using exponential inequalities we apply a chaining technique.