Comment: Microarrays, Empirical Bayes and the Two-Groups Model (2008)
Comment on ``Microarrays, Empirical Bayes and the Two-Groups Model'' [arXiv:0808.0572]
Mouse Cognition-Related Behavior in the Open-Field: Emergence of Places of Attraction (2008)
Anna Dvorkin, Yoav Benjamini, Ilan Golani
Spatial memory is often studied in the Morris Water Maze, where the animal's spatial orientation has been shown to be mainly shaped by distal visual cues. Cognition-related behavior has also been...
Adapting to unknown sparsity by controlling the false discovery rate (2006)
Abramovich, Felix, Benjamini, Yoav, Donoho, David L., Johnstone, Iain M.
We attempt to recover an n-dimensional vector observed in white noise, where n is large and the vector is known to be sparse, but the degree of sparsity is unknown. We consider three different ways...
Adapting to Unknown Sparsity by controlling the False Discovery Rate (2005)
Abramovich, Felix, Benjamini, Yoav, Donoho, David L., Johnstone, Iain M.
We attempt to recover an $n$-dimensional vector observed in white noise, where $n$ is large and the vector is known to be sparse, but the degree of sparsity is unknown. We consider three different...
Ethnic segregation in Tel-Aviv – Jaffa (2004)
In the article analysis of the segregation of 1000 representatives of eight important ethnicgroups in Tel-Aviv – Jaffa is represented. The comparison of results was made on the basisof index of...
John W. Tukey's contributions to multiple comparisons (2002)
This article provides a historical overview of the philosophical, theoretical and practical contributions made by John Tukey to the field of simultaneous inference. His early work, culminating in the...
The control of the false discovery rate in multiple testing under dependency (2001)
Benjamini, Yoav, Yekutieli, Daniel
Benjamini and Hochberg suggest that the false discovery rate may be the appropriate error rate to control in many applied multiple testing problems. A simple procedure was given there as an FDR...
Adaptive Thresholding Of Wavelet Coefficients (2000)
Felix Abramovich, Yoav Benjamini
Wavelet techniques have become an attractive and efficient tool in function estimation. Given noisy data, its discrete wavelet transform is an estimator of the wavelet coefficients. It has been shown...
Adapting to Unknown Sparsity by controlling the False Discovery Rate (2000)
Felix Abramovich, Yoav Benjamini, David Donoho, Iain Johnstone
We attempt to recover a high-dimensional vector observed in white noise, where the vector is known to be sparse, but the degree of sparsity is unknown. We consider three di#erent ways of defining...
Adapting to Unknown Sparsity by controlling the False Discovery Rate (2000)
Felix Abramovich, Yoav Benjamini, David Donoho, Iain Johnstone
We attempt to recover a high-dimensional vector observed in white noise, where the vector is known to be sparse, but the degree of sparsity is unknown. We consider three dierent ways of dening...
Adaptive Thresholding Of Wavelet Coefficients (1999)
Felix Abramovich, Yoav Benjamini
Wavelet techniques have become an attractive and efficient tool in function estimation. Given noisy data, its discrete wavelet transform is an estimator of the wavelet coefficients. It has been shown...
Felix Abramovich, Yoav Benjamini
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...
Thresholding Of Wavelet Coefficients As Multiple Hypotheses Testing Procedure (1997)
Felix Abramovich, Yoav Benjamini
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...
Adaptive Thresholding Of Wavelet Coefficients (1997)
Felix Abramovich, Yoav Benjamini
Wavelet techniques have become an attractive and efficient tool in function estimation. Given noisy data, its discrete wavelet transform is an estimator of the wavelet coefficients. It has been shown...
Genotype–environment interactions in mouse behavior: A way out of the problem
Kafkafi, Neri, Benjamini, Yoav, Sakov, Anat, Elmer, Greg I., Golani, Ilan
In behavior genetics, behavioral patterns of mouse genotypes, such as inbred strains, crosses, and knockouts, are characterized and compared to associate them with particular gene loci. Such genotype...
Quantitative Trait Loci Analysis Using the False Discovery Rate
Benjamini, Yoav, Yekutieli, Daniel
False discovery rate control has become an essential tool in any study that has a very large multiplicity problem. False discovery rate-controlling procedures have also been found to be very...
Genotype–environment interactions in mouse behavior: A way out of the problem
Kafkafi, Neri, Benjamini, Yoav, Sakov, Anat, Elmer, Greg I., Golani, Ilan
In behavior genetics, behavioral patterns of mouse genotypes, such as inbred strains, crosses, and knockouts, are characterized and compared to associate them with particular gene loci. Such genotype...
Quantitative Trait Loci Analysis Using the False Discovery Rate
Benjamini, Yoav, Yekutieli, Daniel
False discovery rate control has become an essential tool in any study that has a very large multiplicity problem. False discovery rate-controlling procedures have also been found to be very...
Mouse Cognition-Related Behavior in the Open-Field: Emergence of Places of Attraction
Dvorkin, Anna, Benjamini, Yoav, Golani, Ilan
Spatial memory is often studied in the Morris Water Maze, where the animal's spatial orientation has been shown to be mainly shaped by distal visual cues. Cognition-related behavior has also been...
Approaches to multiplicity issues in complex research in microarray analysis
Daniel Yekutieli, Anat Reiner-Benaim, Yoav Benjamini, Gregory I. Elmer, Neri Kafkafi, Noah E. Letwin, ...
Adaptive linear step-up procedures that control the false discovery rate
Yoav Benjamini, Abba M. Krieger, Daniel Yekutieli
The linear step-up multiple testing procedure controls the false discovery rate at the desired level q for independent and positively dependent test statistics. When all null hypotheses are true, and...