View source: R/FDX-inference.R

exceedance_inference | R Documentation |

Perform multiple hypothesis testing while controlling the exceedance rate. The exceedance rate is Prob(FDP > bound), where FDP is the false discover proportion defined by the number of false positives devided by the number of total rejections. Small FDP with large number of reject is favorable in practice.

exceedance_inference(profiled_data, alpha, bound)

`profiled_data` |
an exceedance_profile object |

`alpha` |
numeric, the confidence level |

`bound` |
The upper bound of the false discover proportion |

Indices of the hypotheses that are rejected in the procedure.

## The 3rd pvalue statistic param <- param_fast_GW(statistic = "kth_p", param1 = 3) ## generate p-values x <- rbeta(10, 1, 10) ## profile the data profile <- profile_pvalue(x,param) ## compute the 95% confidence envolop alpha <- 0.05 ## reject the first three hypotheses exceedance_confidence(profile, alpha, ri = 3) ## reject the hypothese which pvalues are equal to ## the first three samples. ## In other word, this is equivalent to reject the first three hypotheses exceedance_confidence(profile, alpha, rx = x[1:3]) ## reject the hypotheses which have the lowest 3 p-values exceedance_confidence(profile, alpha, sri = 3) ## Determine which hypotheses can be rejected while controlling the ## exceedance rate: P(FDP > bound) < alpha alpha <- 0.05 bound <- 0.2 exceedance_inference(profile, alpha, bound)

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