  Thermal or finite-size scaling analyses of importance sampling Monte Carlo
time series in the vicinity of phase transition points often combine different
estimates for the same quantity, such as a critical exponent, with the intent
to reduce statistical fluctuations. We point out that the origin of such
estimates in the same time series results in often pronounced
cross-correlations which are usually ignored even in high-precision studies,
generically leading to significant underestimation of statistical fluctuations.
We suggest to use a simple extension of the conventional analysis taking
correlation effects into account, which leads to improved estimators with often
substantially reduced statistical fluctuations at almost no extra cost in terms
of computation time.
