Add to ORKGIn multiple testing, the unknown proportion of true null hypotheses among all null hypotheses that are tested often plays an important role. In adaptive procedures this proportion is estimated and then used to derive more powerful multiple testing procedures
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
to appear in Annals of StatisticsInternational audienceStarting from a parallel between some minimax...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
Many scientific experiments subject to rigorous statistical analysis involve the simultaneous evalua...
The accompanying articles by Dudoit et al. (2003b) and van der Laan et al. (2003) provide single-ste...
Simultaneously testing a collection of null hypotheses about a data generating distribution based on...
In many multiple testing problems, the individual null hypotheses (i) concern univariate parameters ...
The present article proposes two step-down multiple testing procedures for asymptotic control of th...
It is a typical feature of high dimensional data analysis, for example a microarray study, that a re...
We consider multiple testing means of many dependent Normal random variables that do not necessarily...
In the context of multiple hypothesis testing, the proportion p 0 of true null hypotheses in the poo...
Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypot...
Consider the problem of testing s hypotheses simultaneously. The usual approach restricts attention ...
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 ...
to appear in Annals of StatisticsInternational audienceStarting from a parallel between some minimax...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...
Many scientific experiments subject to rigorous statistical analysis involve the simultaneous evalua...
The accompanying articles by Dudoit et al. (2003b) and van der Laan et al. (2003) provide single-ste...
Simultaneously testing a collection of null hypotheses about a data generating distribution based on...
In many multiple testing problems, the individual null hypotheses (i) concern univariate parameters ...
The present article proposes two step-down multiple testing procedures for asymptotic control of th...
It is a typical feature of high dimensional data analysis, for example a microarray study, that a re...
We consider multiple testing means of many dependent Normal random variables that do not necessarily...
In the context of multiple hypothesis testing, the proportion p 0 of true null hypotheses in the poo...
Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypot...
Consider the problem of testing s hypotheses simultaneously. The usual approach restricts attention ...
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 ...
to appear in Annals of StatisticsInternational audienceStarting from a parallel between some minimax...
In multiple hypotheses testing, it is important to control the probability of rejecting true null ...