The conditional independences between variables derived from two independent identically distributed Markov random fields when pairwise order is ignored.
The conditional independences between variables derived from two independent identically distributed Markov random fields when pairwise order is ignored.
复制标题
当忽略成对顺序时，从两个独立的同分布马尔可夫随机场导出的变量之间的条件独立性。
DOI：
10.1093/imammb/dqp022
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Thomas,Alun
中科院分区：
文献类型：
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作者：
Thomas,Alun
将一阶马尔可夫模型中有序和无序向量随机变量的条件独立图等价的一个结果推广到任意森林。这一结果对遗传位点间连锁不平衡图解模型的估计有一定的参考价值。它解释了为什么在条件独立结构方面，有时考虑单倍型还是基因型并不重要。
A result for the equivalence of conditional independence graphs of ordered and unordered vector random variables from first-order Markov models is extended to arbitrary forests. The result is relevant to estimating graphical models for linkage disequilibrium between genetic loci. It explains why, in terms of the conditional independence structure, it sometimes does not matter whether you consider haplotypes or genotypes.