Neyman-Pearson test

Ney·man-Pear·son test

(nē'măn-pēr'sŏn test)
A statistical procedure that assigns different weights to a false-positive result and a false-negative result in an experimental study so as to maximize the power of the study.
References in periodicals archive ?
In Section 4 we propose Neyman-Pearson test which is a most powerful test.
Our aim in this section is to establish nonrandomized Neyman-Pearson test for the hypothesis defined in the preceding section.
Neyman-Pearson test of size [alpha] for testing (59) will reject [H.sub.0], ifand only if
In order to constrain the probability of false alarm, the Neyman-Pearson test requires that the distribution of the detection statistic under [H.sub.0] does not depend on any unknown parameters.
Section 3 introduces the background on Neyman-Pearson test and CS theory.
Neyman-Pearson Test. Statistical hypothesis testing is a crucial method to detect and classify signals.
As adopted in this paper, Neyman-Pearson test could obtain the largest [P.sub.D] under certain constrained [P.sub.F].