Let be the number of rejections by the Benjamini-Hochberg procedure at level , and let be the rejection count after replacing by zero. Then and
If was rejected, lowering its p-value does not change any ordered p-value beyond rank , so . Conversely, if , the other rejected values together with satisfy the original threshold; monotonicity gives . For a valid true-null p-value independent of the others, conditioning on bounds the expectation of the right side by . Summing over true nulls proves false discovery rate at most .
For the Benjamini-Hochberg procedure, replace a true-null p-value by zero and call the new rejection count . The Benjamini-Hochberg leave-one-out identity identifies rejection with with the event and . If is uniform and independent of all the other p-values, each possible rejection count contributes to its expected false-discovery fraction. Summation gives per true null and the displayed exact false discovery rate. Super-uniform independent nulls yield the corresponding upper bound.

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