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The estimate of the precision of the SRM calculated was performed using the Jackknife technique; 95% CI Jackknife SRMs are given in Table 6.
The 95% CI of SRM estimates were calculated using the Jackknife technique [ 26] using the software S-PLUS professional (S-PLUS 6 for Windows; Insightful Corp., Seattle, WA, USA).
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From the simulation results in Figure 6(c) we observe that the TS future prices tend to revert to the mean ((mu= 8.4639)) when we use the jackknife technique to estimate mean reversion.
For this reason, we investigated whether inclusion or exclusion of individual variables (using the "jackknife by variables" technique), and groups of variables (using the "bootstrap by variables technique") materially affect the analysis results.
Quite promising predictions are obtained using the jackknife test and compared with other predictive methods.
Heltshe, J. F. & Forrester, N. E. Estimating species richness using the jackknife procedure.
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.
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.
Means and standard errors were estimated using the jackknife procedure.
Confidence intervals were derived using the jackknife method.
For the regressions used in this study, the jackknife technique was used to estimate standard errors.
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