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Following Gumedze et al. [ 6], we use a parametric bootstrap procedure to obtain the distributions of the LRT statistics (5).
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I calculate the standard error on the marginal effect estimated at the mean using a parametric bootstrap with 1,000 repetitions.
Uncertainty in model parameters was quantified using confidence intervals obtained through bootstrapping the data, and uncertainty in model outputs such as the predicted degree distribution was quantified using a parametric bootstrap.
nfidence intervals for τwere calculated using a parametric bootstrap approach [82].
Standard errors were calculated for the MLE method using a parametric bootstrap.
The significance of the difference in likelihood scores was evaluated using a parametric bootstrap in which 1000 data matrices of 400 bases (the size of the final dataset excluded sites where any individuals had unknown bases) were simulated using the HKY model in Mesquite [75].
We tested the validity of the estimated stepwise expansion model using a parametric bootstrap approach.
The confidence intervals of τ were calculated using a parametric bootstrap approach [ 34].
We tested the validity of the sudden expansion model using a parametric bootstrap approach with 1,000 replicates.
Ninety-five percent (95%%) confidence interval (CI) for each model were calculated by using a parametric bootstrap approach with 1,000 resamples.
The spatial expansion hypothesis (both RI and SSD) was tested using a parametric bootstrap approach (200 replicates).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com