Plots the empirical cumulative distribution function of the p-values related to iterated resampling via bootstrapping or multi-sample splitting.
plotPvals(x, outcome =1, predictor =1, title =TRUE, alpha =0.05)
Arguments
x: Output from resample, given that sampMethod = "bootstrap" or sampMethod = "split".
outcome: Character string or numeric value (in terms of columns in the dataset) to indicate which outcome to plot the p-value distribution for.
predictor: Character string or numeric value (in terms of columns in the dataset) to indicate which predictor to plot the p-value distribution for.
title: If TRUE, then a default title will be given according to the outcome and predictor that are specified. If FALSE, then no title will be plotted. A custom title may also be supplied by the user.
alpha: The false discovery rate. Defaults to .05
Returns
Returns a plot based on the relationship between a particular outcome and predictor.
Details
See Meinshausen, Meier, & Buhlmann (2009) for details.
Examples
x <- resample(ggmDat, sampMethod ="bootstrap")plot(x, what ='pvals')plot(x,'pvals', outcome ='V2', predictor ='V1')
References
Meinshausen, N., Meier, L., & Buhlmann, P. (2009). P-values for high-dimensional regression. Journal of the American Statistical Association. 104, 1671-1681.