Description Usage Arguments Details Value References See Also Examples
Statistical power of soft-thresholding Fisher's p-value combination test under Gaussian mixture model.
1 | power.soft(alpha, n, tau1, eps = 0, mu = 0)
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alpha |
- type-I error rate. |
n |
- dimension parameter, i.e. the number of input p-values. |
tau1 |
- truncation parameter=normalization parameter. tau1 > 0. |
eps |
- mixing parameter of the Gaussian mixture. |
mu |
- mean of non standard Gaussian model. |
We consider the following hypothesis test,
H_0: X_i\sim F_0, H_a: X_i\sim (1-ε)F_0+ε F_1
, where ε is the mixing parameter, F_0 is the standard normal CDF and F = F_1 is the CDF of normal distribution with μ defined by mu and σ = 1.
Power of the soft-thresholding Fisher's p-value combination test.
1. Hong Zhang and Zheyang Wu. "TFisher Tests: Optimal and Adaptive Thresholding for Combining p-Values", submitted.
stat.soft
for the definition of the statistic.
1 2 3 | alpha = 0.05
#If the alternative hypothesis Gaussian mixture with eps = 0.1 and mu = 1.2:#
power.soft(alpha, 100, 0.05, eps = 0.1, mu = 1.2)
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