apf_plot: Generate smooth graphs for the APF and FDR estimates

In APFr: Multiple Testing Approach using Average Power Function (APF) and Bayes FDR Robust Estimation

Description

apf_plot returns a graph with Average Power Function (APF), Bayes False Discovery Rate (FDR) and APF vs. FDR. In addition, when tab = TRUE, a table containing APF, FDR, tau and gamma values for a selected subset of APF and FDR is printed.

Usage

apf_plot(APF_lst, tab = TRUE, APF_inf = 0.5, FDR_sup = 0.05)

Arguments

APF_lst	The output from the apf_fdr function.
tab	If TRUE, a table with relevant values of APF, FDR, tau and gamma is printed.
APF_inf	Sets the minimum value of APF to appear in the table when tab = TRUE.
FDR_sup	Sets the maximum value of Bayes FDR to appear in the table when tab = TRUE.

Value

Smooth graphs for APF vs Gamma (left), FDR vs Gamma (centre) and APF vs FDR (right). Regions where FDR ≤ FDR_sup and APF ≥ APF_inf (if presents) are highlighted in yellow and printed in a table (if tab = TRUE) together with the relative values of gamma and tau.

References

Quatto, P, Margaritella, N, et al. Brain networks construction using Bayes FDR and average power function. Stat Methods Med Res. Published online May 14th, 2019; DOI:10.1177/0962280219844288.

Examples

data("Ex2")
apf_plot(Ex2)
# Ex2 is an example of output obtained
# from the apf_fdr() function.

APFr documentation built on June 18, 2019, 5:05 p.m.