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On a variance stabilizing model and its application to genomic data

机译:方差稳定模型及其在基因组数据中的应用

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摘要

In this paper, we propose a model based on a class of symmetric distributions, which avoids the transformation of data, stabilizes the variance of the observations, and provides robust estimation of parameters and high flexibility for modeling different types of data. Probabilistic and statistical aspects of this new model are developed throughout the article, which include mathematical properties, estimation of parameters and inference. The obtained results are illustrated by means of real genomic data.
机译:在本文中,我们提出了一种基于一类对称分布的模型,该模型避免了数据的转换,稳定了观测值的方差,并提供了可靠的参数估计和为不同类型的数据建模提供的高度灵活性。在整个文章中,都会开发此新模型的概率和统计方面,包括数学属性,参数估计和推论。所得结果通过真实的基因组数据进行说明。

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