对"统计分类使得基于凝聚的鸟类树的准确估计"的评论的回应
Siavash Mirarab1, Md Shamsuzzoha Bayzid2, Bastien Boussau3
1Department of Computer Science, University of Texas at Austin, Austin, TX, USA. Department of Electrical and Computer Engineering, University of California at San Diego, San Diego, CA, USA.
概括
这项研究驳斥了对物种树估计加权统计分类的说法. 我们的分析表明先前的数学论证和模拟方法有缺陷,导致对该技术有偏见的结果.
科学领域:
- 遗传学
- 计算生物学
- 统计模型
背景情况:
- 权重统计分类是一种用于遗传学分析的方法.
- 和爱德华兹最近的一项研究质疑其在物种树木估计中的有用性.
研究的目的:
- 解决和爱德华兹关于加权统计分类的批评.
- 在物种树估计中证明加权统计分类的有效性和有效性.
主要方法:
- 对加权统计区分的论点进行数学重新评估.
- 分析和爱德华兹使用的模拟研究方法.
- 使用修正的统计分类协议对结果进行比较.
主要成果:
- 和爱德华兹提出的数学论证不适用于加权统计分类.
- 和爱德华兹的模拟研究偏离了标准协议并使用了有偏见的数据.
- 统计分类的正确应用产生了有效的结果.
结论:
- 权重统计分类仍然是物种树估计的有效方法.
- 和爱德华兹的批评是基于错误的数学推理和模拟方法.
- 进一步的研究应采用标准化方案来评估遗传学方法.
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