On the asymptotic normality of kernel density estimators for causal linear random fields

We establish sufficient conditions for the asymptotic normality of kernel density estimators applied to causal linear random fields, by m -dependent approximation. Our conditions on the coefficients of linear random fields are weaker than the known results, although our assumption on the bandwidth is not minimal. We also establish a convergence rate of Berry–Esseen’s type.