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Given low occurrence data samples, we tested model predictions using the jackknife manipulation proposed by Pearson et al. [71], the only robust test for evaluating models based on small samples: N−1 points are used to develop N jackknifed models.
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Heltshe, J. F. & Forrester, N. E. Estimating species richness using the jackknife procedure.
Quite promising predictions are obtained using the jackknife test and compared with other predictive methods.
Total species richness at the regional level was calculated by extrapolating the species-area curves (Supplementary Figs 4 7) using the jackknife method of first order54.
There is not clear or unanimous support for using the jackknife approach when using subsets of the data or complex, multivariate analyses.
Means and standard errors were estimated using the jackknife procedure.
Confidence intervals were derived using the jackknife method.
The estimate of the precision of the SRM calculated was performed using the Jackknife technique; 95% CI Jackknife SRMs are given in Table 6.
Areas under the ROC curves were compared using the jackknife method proposed by DeLong et al. [ 36].
Branch support was evaluated using the Jackknife method and calculating decay indexes for each node (Bremer support).
The difference between the survival percentages of single- and multiple-surface restorations was tested using the jackknife SE.
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