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DNA序列异质性评估中的若干统计问题AI 解读

The fields of molecular genetics and medicine are accumulating DNA and protein sequence data at an accelerating rate. Discovering and interpreting sequence patterns can contribute to understanding molecular mechanisms and evolutionary processes. This article considers two types of statistical problems in these contexts: (1) identifying anomalies in the distribution of a specified biochemical marker along a DNA string; in particular, new statistical methods are set forth by…

评估 DNA 序列非均匀性的若干统计问题AI 解读

The fields of molecular genetics and medicine are accumulating DNA and protein sequence data at an accelerating rate. Discovering and interpreting sequence patterns can contribute to understanding molecular mechanisms and evolutionary processes. This article considers two types of statistical problems in these contexts: (1) identifying anomalies in the distribution of a specified biochemical marker along a DNA string; in particular, new statistical methods are set forth by…

多元正态变量绝对值的全正性及其置信集与概率不等式应用AI 解读

Total positivity properties of multivariate densities are useful in deducing positive dependence of random vector components and related probability inequalities. In this paper we determine necessary and sufficient conditions for total positivity of absolute value multinormal variables. The results are applied to obtain positive dependence and associated inequalities for the multinormal and related distributions, e.g., the multivariate $t$ and Wishart distributions.…

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具有单调似然比的分布AI 解读

A sufficient condition for the validity of the commonly used one-sided tests is that the underlying density p(x, ω), where x is the observed variable and ω the unknown parameter, possess a “monotone likelihood ratio.” In estimation, only monotone functions of the observed variable x should be used as possible estimating functions of ω.

具有单调似然比的分布AI 解读

A sufficient condition for the validity of the commonly used one-sided tests is that the underlying density p(x, ω), where x is the observed variable and ω the unknown parameter, possess a “monotone likelihood ratio.” In estimation, only monotone functions of the observed variable x should be used as possible estimating functions of ω.