The 2006 CSDA paper is really very informative, perhaps, I'm trying to understand the things lying beyond. If we have e.g. k=3, then taking nproc=3 for the functional maxBB we get a critical value (boundary)
maxBB$computeCritval(0.05,nproc=3) [1] 1.544421, and this for nproc=NULL (Bonferroni approximation) will be maxBB$computeCritval(0.05) [1] 1.358099. Aggregating 3 Brownian bridges first over components, we obtain time series process. Now, we wonder if maximum value of the process (aggregation over time) lies over boundary. Which boundary - 1.544421 or 1.358099 - should one take? They look too different and, for instance, lead to "unfair computing" of empirical size (as rejection rate of null hypothesis) or empirical power (as acception rate of alternative). -- View this message in context: http://r.789695.n4.nabble.com/nproc-parameter-in-efpFunctional-tp3972419p3989598.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
