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Ninety-five perconfidencedence intervals for such effects can be found using bootstrap techniques.
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Confidence intervals for the locations of significant QTL were found using bootstrap methods [ 52] using 500 replicates.
Confidence intervals can be found using standard bootstrap techniques.
Mean and 95% confidence parameter estimates for these data sets were found using mixed-effects model regression followed by bootstrap analysis.
However, for small samples (around n=10), applying the correct parametric procedure is better than using bootstrapping, provided that a good distributional fit can be found.
Bootstrap solutions can be found in 11 and 12.
PhyML was run with 100 bootstraps and implemented differently depending on the substitution model and parameters found using Prottest.
A more detailed description of the statistical analysis using Bootstrapping is found in Appendix A. Statistical analysis was performed using the R, version 3.0.1.
No demographic variable was found to be bootstrap significant.
The robustness of the models was evaluated using bootstrap techniques.
The web interface is developed using BootStrap (http://twitter.github.com/bootstrap).
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