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The Cavalli-Sforza and Edwards genetic distance [16] was calculated among the 36 subclusters identified (with Structure) and utilized to construct a neighbor joining tree after 10,000 bootstrap estimations on the 96 loci retained using Populations [46].
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MTP is based on Bootstrap estimation of the null distribution samples and the data generating distribution P. Samples are drawn at random with replacement from the observed data.
Bootstrap estimations validated the models.
Moreover, such percentiles have low variance, low dependence on sample size, and are amenable to bootstrap estimations of confidence intervals, when compared to the largest individual per sample [ 108].
Bootstrap estimations of 95% confidence intervals for the averages and medians are also shown.
To reduce this, the use of unitary weighting and bootstrap estimations of confidence intervals are presented.
Note however, that the bootstrap method comes with a high computational cost since it requires a large number of parameter estimations on the same model structure using different data set with added random noise at a certain noise level.
In the bootstrap estimation 1000 bootstrap replications are used to produce the bootstrap distribution of PR.
The bootstrap estimation and modified Jacknife test were used to derive 95% confidence intervals for differences in the responsiveness estimates.
If the bootstrap estimation is roughly correct, then aggregating would reduce variance without increasing bias.
Consistent with present results, they found that both estimators were equally efficient (based on their results from bootstrap estimation of standard errors) and both were appreciably more efficient than results obtained using simple random sampling by at least 24%, rising to as much as 61% as sample size increased.
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