间隙测量测试及其在数据完整性验证中的应用
Gap-Measure Tests with Applications to Data Integrity Verification
摘要：
在本文中，我们提出并检查间隙统计评估均匀分布假设。我们提供了相关的数据完整性测试的例子，最大差距统计提供更大的灵敏度比卡方（$χ^2$），从而允许新的测试被用来代替或作为一个补充$χ^2$测试的目的，区分一个更大的类的偏差从均匀性。我们建立了建议的最大间隙测试具有相同的顺序和并行计算复杂度的$χ^2$，因此适用于大数据分析和完整性验证。
英文摘要：
In this paper we propose and examine gap statistics for assessing uniform distribution hypotheses. We provide examples relevant to data integrity testing for which max-gap statistics provide greater sensitivity than chi-square ($χ^2$), thus allowing the new test to be used in place of or as a complement to $χ^2$ testing for purposes of distinguishing a larger class of deviations from uniformity. We establish that the proposed max-gap test has the same sequential and parallel computational complexity as $χ^2$ and thus is applicable for Big Data analytics and integrity verification.
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