Description Usage Arguments Details Value References See Also Examples

View source: R/power.tfisher.R

Statistical power of thresholding Fisher's p-value combination test under Gaussian mixture model.

1 | ```
power.tfisher(alpha, n, tau1, tau2, eps = 0, mu = 0)
``` |

`alpha` |
- type-I error rate. |

`n` |
- dimension parameter, i.e. the number of input p-values. |

`tau1` |
- truncation parameter. 0 < tau1 <= 1. |

`tau2` |
- normalization parameter. tau2 >= tau1. |

`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 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.tfisher`

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.tfisher(alpha, 100, 0.05, 0.25, eps = 0.1, mu = 1.2)
``` |

TFisher documentation built on March 21, 2018, 5:11 p.m.

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