The jackknife method is a statistical resampling technique used to estimate the bias and variance of a statistical estimator. By systematically leaving out one observation from the dataset at a time and calculating the estimator, this method helps provide insights into the stability and reliability of the results obtained from the data, which is particularly important in maximizing parsimony.
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