Estimation of distribution overlap of urn models.
Estimation of distribution overlap of urn models.
复制标题
DOI：
10.1371/journal.pone.0042368
复制
发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Lladser ME
中科院分区：
文献类型：
--
作者：
Hampton J;Lladser ME
统计学中的一个经典问题是估计样本的预期覆盖率，这在基因表达，微生物生态学，优化甚至钱币学中都有应用。在这里，我们考虑一个相关的扩展这个问题的随机样本的两个离散分布。具体来说，我们估计我们称之为样本的相异度概率，即，从一个分布中抽取的概率在从另一个分布中抽取时没有被观察到。我们证明了我们的相异性的估计是一个统计量和一致的最小方差无偏估计的相异性的最大适当的范围。此外，尽管非马尔可夫性质，我们的估计时，按顺序应用，我们表明它收敛均匀的概率相异性参数，我们提出的标准时，它是近似正态分布，并承认一致的刀切估计其方差。作为概念证明，我们分析V35 16S rRNA数据以区分各种微生物环境。其他潜在的应用涉及任何情况下，两个离散分布的相异性可能是感兴趣的。例如，在SELEX实验中，每个瓮可以代表一个随机的RNA库，每个瓮可以针对该库中的特定结合位点问题得出一个可能的解决方案。然后，这些池的相异性与在一个池中找到另一个池中不存在的结合位点解决方案的概率相关。
A classical problem in statistics is estimating the expected coverage of a sample, which has had applications in gene expression, microbial ecology, optimization, and even numismatics. Here we consider a related extension of this problem to random samples of two discrete distributions. Specifically, we estimate what we call the dissimilarity probability of a sample, i.e., the probability of a draw from one distribution not being observed in draws from another distribution. We show our estimator of dissimilarity to be a -statistic and a uniformly minimum variance unbiased estimator of dissimilarity over the largest appropriate range of . Furthermore, despite the non-Markovian nature of our estimator when applied sequentially over , we show it converges uniformly in probability to the dissimilarity parameter, and we present criteria when it is approximately normally distributed and admits a consistent jackknife estimator of its variance. As proof of concept, we analyze V35 16S rRNA data to discern between various microbial environments. Other potential applications concern any situation where dissimilarity of two discrete distributions may be of interest. For instance, in SELEX experiments, each urn could represent a random RNA pool and each draw a possible solution to a particular binding site problem over that pool. The dissimilarity of these pools is then related to the probability of finding binding site solutions in one pool that are absent in the other.
登录
查看更多内容
影响因子：
3.7
作者：
Lladser ME;Gouet R;Reeder J
通讯作者：
Reeder J
DOI：
10.1198/016214504000001709
发表时间：
2004-12-01
影响因子：
3.7
作者：
Mao, CX
通讯作者：
Mao, CX
影响因子：
4.5
作者：
EFRON, B;STEIN, C
通讯作者：
STEIN, C
影响因子：
--
作者：
HOEFFDING, W
通讯作者：
HOEFFDING, W
影响因子：
2.7
作者：
GOOD, IJ
通讯作者：
GOOD, IJ