A uniform Berry--Esseen theorem on $M$-estimators for geometrically ergodic Markov chains

Abstract: Let ${X_n}{n\ge0}$ be a $V$-geometrically ergodic Markov chain. Given some real-valued functional $F$, define $M_n(\alpha):=n^{-1}\sum{k=1}^nF(\alpha,X_{k-1},X_k)$, $\alpha\in\mathcal{A}\subset \mathbb {R}$. Consider an $M$ estimator $\hat{\alpha}n$, that is, a measurable function of the observations satisfying $M_n(\hat{\alpha}_n)\leq \min{\alpha\in\mathcal{A}}M_n(\alpha)+c_n$ with ${c_n}_{n\geq1}$ some sequence of real numbers going to zero. Under some standard regularity and moment assumptions, close to those of the i.i.d. case, the estimator $\hat{\alpha}_n$ satisfies a Berry--Esseen theorem uniformly with respect to the underlying probability distribution of the Markov chain.