An extension of a result of Csiszár.
Strassen's invariance principle for additive functionals of Markov chains with spectral gap in the Wasserstein metric is proved.
Invariance principle in is studied using signed random measures. This approach to the problem uses an explicit isometry between and a reproducing kernel Hilbert space giving a very convenient setting for the study of compactness and convergence of the sequence of Donsker functions. As an application, we prove a version of the invariance principle in the case of -mixing random variables. Our result is not available in the -setting.