Non-Uniform Sampling of Fixed Margin Binary Matrices
Non-Uniform Sampling of Fixed Margin Binary Matrices
复制标题
固定边距二元矩阵的非均匀采样
DOI：
10.1145/3412815.3416887
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Hitt, Matthew P.
中科院分区：
文献类型：
--
作者：
Fout, Alex;Fosdick, Bailey K.;Hitt, Matthew P.
二进制矩阵形式的数据集在科学领域中无处不在，研究人员通常对识别和量化值得注意的结构感兴趣。一种方法是将观察到的数据与在零模型下可能获得的数据进行比较。在这里，我们考虑从满足一组边际行和列和的二进制矩阵的空间采样。而现有的采样方法集中在均匀采样从这个空间，我们介绍了修改后的版本的两个elementwise交换算法，根据定义的权重矩阵，这给出了一个相对概率为每个条目的非均匀概率分布的样本。我们证明，零值的权重矩阵，即结构零，一般是有问题的交换算法，除非当他们有特殊的单调结构。我们通过模拟研究探索我们的算法的属性，并说明了采用非均匀空模型使用经典的鸟类栖息地数据集的潜在影响。
Data sets in the form of binary matrices are ubiquitous across scientific domains, and researchers are often interested in identifying and quantifying noteworthy structure. One approach is to compare the observed data to that which might be obtained under a null model. Here we consider sampling from the space of binary matrices which satisfy a set of marginal row and column sums. Whereas existing sampling methods have focused on uniform sampling from this space, we introduce modified versions of two elementwise swapping algorithms which sample according to a non-uniform probability distribution defined by a weight matrix, which gives the relative probability of a one for each entry. We demonstrate that values of zero in the weight matrix, i.e. structural zeros, are generally problematic for swapping algorithms, except when they have special monotonic structure. We explore the properties of our algorithms through simulation studies, and illustrate the potential impact of employing a non-uniform null model using a classic bird habitation dataset.
影响因子：
2.7
作者：
Alan Roberts;L. Stone
通讯作者：
L. Stone
DOI：
10.1198/016214504000001303
发表时间：
2005-03-01
影响因子：
3.7
作者：
Chen, YG;Diaconis, P;Liu, JS
通讯作者：
Liu, JS