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2 results for p-filter

Unified algorithm for incorporating various prior knowledge in multiple testing.

problem Improving power and precision in multiple testing procedures with prior knowledge.
method p-filter algorithm that incorporates four types of prior knowledge: null hypotheses, penalties, groups, and independence.
result Unified framework allows for recovery of various known algorithms.

In many practical applications of multiple hypothesis testing using the False Discovery Rate (FDR), the given hypotheses can be naturally partitioned into groups, and one may not only want to control the number of false discoveries (wrongly rejected null hypotheses), but also the number of falsely discovered groups of …

2015-12-10abs ↗pdf ↗