Just out @ Paleobiology
Estimating the number of pulses in a mass extinction
Steve C. Wang and Ling Zhong
Using a two-step algorithm, we are able to estimate not just the number of extinction pulses but also a confidence level or posterior probability for each possible number of pulses. In the first step, we find the maximum likelihood estimate for each possible number of pulses. In the second step, we calculate the Akaike information criterion and Bayesian information criterion weights for each possible number of pulses, and then apply a k-nearest neighbor classifier to these weights. This method gives us a vector of confidence levels for the number of extinction pulses—for instance, we might be 80% confident that there was a single extinction pulse, 15% confident that there were two pulses, and 5% confident that there were three pulses. Equivalently, we can state that we are 95% confident that the number of extinction pulses is one or two. Using simulation studies, we show that the method performs well in a variety of situations, although it has difficulty in the case of decreasing fossil recovery potential, and it is most effective for small numbers of pulses unless the sample size is large. We demonstrate the method using a data set of Late Cretaceous ammonites.
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