拟最优权在异常搜索中的应用。累积谱中台阶状异常的统计判据
Application of quasi-optimal weights to searches of anomalies. Statistical criteria for step-like anomalies in cumulative spectra
摘要：
准最优权重的统计方法可用于导出异常搜索的标准。作为一个例子，我们推导出一个方便的统计标准，如在Troitsk-nu-质量，美因茨和KATRIN实验中测量的累积光谱的阶梯状异常。它几乎与零假设附近的局部最强检验一样有效，并且明显优于传统的卡方检验和柯尔莫哥洛夫-斯米尔诺夫检验。它还与“邻居的成对相关性”的特设标准进行了比较;后者被认为是不太强大的，如果更敏感的更一般的异常。作为一个现实的例子，标准适用于Troitsk-nu-mass数据。
英文摘要：
The statistical method of quasi-optimal weights can be used to derive criteria for searches of anomalies. As an example we derive a convenient statistical criterion for step-like anomalies in cumulative spectra such as measured in the Troitsk-nu-mass, Mainz and KATRIN experiments. It is almost as powerful as the locally most powerful one near the null hypothesis and appreciably excels the conventional chi^2 and Kolmogorov-Smirnov tests. It is also compared with an ad hoc criterion of «pairwise correlations of neighbours»; the latter is seen to be less powerful if more sensitive to more general anomalies. As a realistic example, the criteria are applied to the Troitsk-nu-mass data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
