Higher Criticism for Large-Scale Inference, Especially for Rare and Weak Effects
نویسندگان
چکیده
منابع مشابه
Higher Criticism for Large-Scale Inference, Especially for Rare and Weak Effects
In modern high-throughput data analysis, researchers perform a large number of statistical tests, expecting to find perhaps a small fraction of significant effects against a predominantly null background. Higher Criticism (HC) was introduced to determine whether there are any nonzero effects; more recently, it was applied to feature selection, where it provides a method for selecting useful pre...
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Genome-wide association studies (GWAS) have identified many genetic factors underlying complex human traits. However, these factors have explained only a small fraction of these traits’ genetic heritability. It is argued that many more genetic factors remain undiscovered. These genetic factors likely are weakly associated at the population level and sparsely distributed across the genome. In th...
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Often when we deal with ‘Big Data’, the true effects we are interested in are Rare and Weak (RW). Researchers measure a large number of features, hoping to find perhaps only a small fraction of them to be relevant to the research in question; the effect sizes of the relevant features are individually small so the true effects are not strong enough to stand out for themselves. Higher Criticism (...
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Signal identification in large-dimensional settings is a challenging problem in biostatistics. Recently, the method of higher criticism (HC) was shown to be an effective means for determining appropriate decision thresholds. Here, we study HC from a false discovery rate (FDR) perspective. We show that the HC threshold may be viewed as an approximation to a natural class boundary (CB) in two-cla...
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ژورنال
عنوان ژورنال: Statistical Science
سال: 2015
ISSN: 0883-4237
DOI: 10.1214/14-sts506