Showing papers by "Yoav Benjamini published in 1995"
TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Abstract: SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
83,420 citations
TL;DR: This fitted model may be useful in distinguishing between newly diagnosed young patients who will undergo remission, requiring lower insulin doses, and those who have little chance for remission, and it might also be helpful in the selection of patients most likely to benefit from immunosuppression or modulation, to maximize the benefit to risk ratio for such patients.
246 citations
01 Jan 1995
TL;DR: In this paper, the authors proposed a global threshold for finite discrete wavelet transform estimator, which asymptotically reduces the expected risk of the corresponding wavelet estimator close to the possible minimum.
Abstract: Given noisy signal, its finite discrete wavelet transform is an estimator of signal’s wavelet expansion coefficients. An appropriate thresholding of coefficients for further reconstruction of de-noised signal plays a key-role in the wavelet decomposition/reconstruction procedure. [DJ1] proposed a global threshold\( \lambda = \sigma \sqrt {{2\log n}} \) and showed that such a threshold asymptotically reduces the expected risk of the corresponding wavelet estimator close to the possible minimum. To apply their threshold for finite samples they suggested to always keep coefficients of the first coarse j0 levels.
94 citations
TL;DR: In this article, the appropriate class of skewed distributions for which each of the tests of symmetry is consistent was found, and the results were used to determine whether a distribution is symmetric or skewed.
Abstract: It is important to determine whether a distribution is symmetric or skewed, as this might affect inferences of interest. There are a number of concepts that define classes of skewed distributions, and many tests for symmetry have been suggested in the literature. We find the appropriate class of skewed distributions for which each of the tests of symmetry is consistent.
3 citations