A test for the presence of covariance between time‐uncertain series of data with application to the Dongge Cave speleothem and atmospheric radiocarbon records

Statistical measures of the relationships between time series are generally altered by the presence of errors in timing, i.e., when applied to time‐uncertain series. For example, the covariance sampled between two time series which in truth covary will generally be decreased by errors in timing. Most previous work on this subject has sought to maximize some goodness of fit between time‐uncertain series either heuristically or through more quantitative methods. However, there is a danger that unrelated records can be made to appear to covary by time adjustment. Here we propose a statistical test for the presence of covariance between time‐uncertain series wherein the probability of obtaining a maximum covariance from randomly realized time‐uncertain series is assessed using the theory of order statistics. The results of this analytical method provide insight into the influence of timing errors upon covariance and are shown to be consistent with results derived from a Monte Carlo procedure. We apply this methodology to evaluate the covariance between a time‐uncertain stalagmite record and atmospheric radiocarbon during the Holocene and find, contradictory to previous interpretation, that there is insignificant covariance between the two at the 95% confidence level.