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.