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With this in thoughts, we carried out a big simulation study to analyze the impact of chronological uncertainty on a potentially useful time-series methodology. The method is a type of regression involving a prediction algorithm referred to as the Poisson Exponentially Weighted Moving Average (PEMWA). It is designed for use with depend time-series knowledge, which makes it applicable to a wide range of questions about human-environment interplay in deep time. Our simulations recommend that the PEWMA technique can often appropriately how much is say hi dating establish relationships between time-series regardless of chronological uncertainty. When two time-series are correlated with a coefficient of 0.25, the method is able to establish that relationship correctly 20–30% of the time, offering the time-series comprise low noise ranges. With correlations of round zero.5, it’s capable of correctly identifying correlations despite chronological uncertainty greater than 90% of the time.