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MLE parameters and goodness-of-fit results for artifact count data.

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NIAID Data Ecosystem2026-03-09 收录
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https://figshare.com/articles/dataset/_MLE_parameters_and_goodness_of_fit_results_for_artifact_count_data_/1594296
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*Plausible models at p > 0.10. aIn some cases, the methods described above yield a p-value in the range of statistical plausibility but a power-law scaling parameter that exceeds the upper limit of acceptable values (α≤ 3). Such values are theoretically problematic because they describe distributions that are not scale invariant and thus converge on non-power law distributions [15]. Moreover, such values are greater than those found to describe settlement hierarchy in the empirical cases of complex societies. For these reasons, an otherwise statistically plausible power-law model is rejected if the scaling parameter is greater than or equal to three. MLE parameters and goodness-of-fit results for artifact count data.
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