Rates of convergence in the central limit theorem for Banach valued dependent variables

We provide rates of convergence in the central limit theorem in terms of projective criteria for adapted stationary sequences of centered random variables taking values in Banach spaces, with finite moment of order $p\in ]2,3]$ as soon as the central limit theorem holds for the partial sum normalized by $n^{-1\mathrm{/}2}$. This result applies to the empirical distribution function in $L^p(\mu )$, where $p\ge 2$ and $\mu$ is a real $\sigma$-finite measure: under some $\tau$-mixing conditions we obtain a rate of order $O(n^{-(p-2)\mathrm{/}2})$. In the real case, our result leads to new conditions to reach the optimal rates of convergence in terms of Wasserstein distances of order $p\in ]2,3]$.