In multiple testing, a variety of control metrics have been introduced such as the family-wise error rate (FWER), the False Discovery Rate (FDR), False Exceedence Rate (FER), etc. We found a way to embed these metrics into a continuous family of control metrics, all of which can be attained by applying a simple and general family of multiple testing procedures. The new general error rate (GER) limits the number of false positives relative to an arbitrary increasing function of the number of rejections. An example is $FR/R^\gamma$, the number of false rejections divided by the number of rejections to a power $0\leq \gamma\leq 1$. We investigated both the control of quantiles and of expectations and provide the corresponding multiple testing ...
ABSTRACT. We present a unifying approach to multiple testing procedures for sequential (or streaming...
Statistical hypothesis testing is used while analyzing experimental data. This thesis is focused on ...
Popular procedures to control the chance of making type I errors when multiple statistical tests are...
Given the large number of papers written over the last ten years on error controls in high dimension...
Consider the problem of testing s hypotheses simultaneously. The usual approach restricts attention ...
Over the last two decades, a large variety of type I error rates and control procedures have been pr...
a practical and powerful Approach to multiple Testing ’ by benjamini et. al.[1] proposes a new frame...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
The accompanying articles by Dudoit et al. (2003b) and van der Laan et al. (2003) provide single-ste...
International audienceMultiple testing issues have long been considered almost exclusively in the co...
The present article proposes general single-step multiple testing procedures for controlling Type I ...
Summary. Multiple-hypothesis testing involves guarding against much more complicated errors than sin...
ABSTRACT. We present a unifying approach to multiple testing procedures for sequential (or streaming...
Statistical hypothesis testing is used while analyzing experimental data. This thesis is focused on ...
Popular procedures to control the chance of making type I errors when multiple statistical tests are...
Given the large number of papers written over the last ten years on error controls in high dimension...
Consider the problem of testing s hypotheses simultaneously. The usual approach restricts attention ...
Over the last two decades, a large variety of type I error rates and control procedures have been pr...
a practical and powerful Approach to multiple Testing ’ by benjamini et. al.[1] proposes a new frame...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
The accompanying articles by Dudoit et al. (2003b) and van der Laan et al. (2003) provide single-ste...
International audienceMultiple testing issues have long been considered almost exclusively in the co...
The present article proposes general single-step multiple testing procedures for controlling Type I ...
Summary. Multiple-hypothesis testing involves guarding against much more complicated errors than sin...
ABSTRACT. We present a unifying approach to multiple testing procedures for sequential (or streaming...
Statistical hypothesis testing is used while analyzing experimental data. This thesis is focused on ...
Popular procedures to control the chance of making type I errors when multiple statistical tests are...