I have $m$ weakly stationary observations $X_1,X_2,\cdots,X_m$. I don't know anything else about the observations. I want to estimate the variance of the sample mean. At first, my idea was to use nonparametric bootstrapping to do this. But I learnt that this method doesn't work for correlated data.
What are the most easy, standard ways of doing this to get reliable estimates?