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GroupTest (version 1.0.1)

GT.wrapper: Multiple testing procedure for the grouped hypothesis

Description

This function is the main function to perform the two-stage testing for the grouped hypotheses.

Usage

GT.wrapper(TestStatistic, alpha = 0.05, eta = alpha, pi1.ini = 0.7, pi2.1.ini = 0.4, L = 2, muL.ini = c(-1, 1), sigmaL.ini = c(1, 1), cL.ini = c(0.5, 0.5), DELTA = 0.001, sigma.KNOWN=FALSE)

Arguments

TestStatistic
An array of list. Each list of the array corresponds to one group, containing the test statistic, stored as X, and the group size, stored as mg.
alpha
the targeted FDR level. By default, it is chosen as 0.05.
eta
the targeted FDR level within each group. The default and recommended choice is alpha. By default, it is chosen as $\alpha$.
pi1.ini
Initial value: the probability that a group is significant. By default, it is chosen as 0.7
pi2.1.ini
Initial value: the probability that an individual null hypothesis is false given that the group is significant. By default, it is chosen as 0.4.
L
The number of Gaussian component under the alternative hypothesis. By default, it is chosen as 2.
muL.ini
Initial value: a vector of means for all the components of the Gaussian mixture. By default, is is chosen as -1 and 1.
sigmaL.ini
Initial value: a vector of standard deviation of all the components of the Gaussian mixture. By default, it is chosen as 1 and 1.
cL.ini
Initial value: a vector of the probability for all the components of the Gaussian mixture. By default, it is chosen as 50% and 50%.
DELTA
The criteria to stop the EM algorithm. In this algorithm, we calcualte the maximum of absolution difference of the current estiamted value and its previous value for the parameters. By default, it is chosen as 0.0001.
sigma.KNOWN
The boolean variable, indicating whether the variance is known. Be default, it is chosen as FALSE.

Value

The function returns a TSGroupTest object. It contains
parameter
this is a list, consisting of estimated parameters based on the EM algorithm. The elements are $\pi_1$, $\pi_{2|1}$, $c_l$, $\mu_l$, $\sigma_l$.
TSGroupTest[[g]]
all the quntities regarding the g-th group, including the test statistic within this group, the individual conditional local fdr score ($ P(\theta_{gj}=0|x, \theta_{g}=1)$), the group-wise local fdr score ($P(\theta_g=0|x)$), between-group decision, within-group decision

Examples

Run this code
data(GroupTest_simulate)

GT.Test <- GT.wrapper( GroupTest_simulate, alpha=0.05, eta=alpha,
pi1.ini=0.7, pi2.1.ini=0.4, L=2, muL.ini=c(-1,1), sigmaL.ini=c(1,2),
cL.ini=c(0.4,0.6), DELTA=0.001, sigma.KNOWN=FALSE )

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