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When α is large, the method detects very few outliers.
When the pathway length becomes too large, the method produces many highly overlapping results.
If the frequency \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document} is not sufficiently large, the method of averaging fails, and HFS may cause more complicated effects than those presented in Fig. 1.
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When the number of unmixed individuals is large, the methods recover ancestry well, and the number of admixed individuals has no effect on accuracy.
Generally, its accuracy increases when the number of collocation points is large and the method tends to be stable.
By appropriately selecting one of these large bands, the method provided some grade of specificity.
However, in large populations, the method was incapable of providing precise estimates of N e, given our sample sizes.
You may also make them into a large circle, the method is flexible.
To compare the variance of the larger Σω90° with that of the larger Σω45°, the method and the extended t-test described by Zar were used ([37], Section 9.4, pp. 182 183).
From the simulation result, when α is small and γ is large, the proposed method shows the good BER performance.
From the simulation result, when α is small and γ is large, the proposed method shows the good BER performance as same Figure 5.
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