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Confidence limits for parameter estimates were obtained by bootstrap sampling, with replacement, from the actual data, with individual condors as bootstrap sampling units.
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This method uses multiple versions of a training set on different models by using the bootstrap (sampling with replacement).
This procedure yields a sex-averaged rate of R = 5.9 × 10−6 per bp per meiosis (and a 95% confidence interval [CI] of 4.6 × 10−6 7.4 × 10−6, calculated by 40,000 bootstrap samples with 10 Mb blocks).
ANCOVA test was used, followed by pairwise comparison using 1,000 stratified bootstrap samples with bias corrected and accelerated (BCa) 95% CI for multiple testing bias corrections due to deviation of normality.
Confidence intervals for the differences in logistic regression coefficients were approximated by a bootstrap technique with 2000 random bootstrap samples with replacement [ 31].
Standard errors for the elements of are obtained by calculating the corresponding standard deviations over bootstrap samples, (with, e.g. R = 250 or R = 500).
We drew a bootstrap sample, with replacement, from the data contributed by the 60 individual condors, with individual birds as bootstrap units.
A probabilistic sensitivity analysis was informed by a multi-stage bootstrapping (sampling with replacement) process, which precluded the need to parameterize the correlation between lifetime costs and survival.
The statistical validity of the neighbor-joining trees was assessed by bootstrap re-sampling with 1000 replicates.
LogicFS is preset by 20 iterations with bootstrap sampling.
The major steps of the CPF approach with bootstrap sampling are summarized by the following pseudocode.
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