Compute the TFCE correction given a matrix a permuted statistical signals.
compute_tfce(distribution, alternative = "greater", E = 0.5, H = 1, ndh)A matrix of permuted statistical signal. The first row indicating the observed statistics.
A character string indicating the alternative hypothesis. Default is "greater". Choose between "greater", "less" or "two.sided".
A scalar that represent the extend parameter of the TFCE transformation. Default is E = 0.5.
A scalar that represent the height parameter of the TFCE transformation. Default is H = 1.
The number of terms in the approximation of the integral.
The approximation of the TFCE integral starts from the minimal statistic (among the permuted statistic), not 0. Indeed, the value of the integral (from 0, to this minimal value) is the same for all time points, all permutations and does not need to be computed to get p-values.
Other multcomp:
compute_clusterdepth_head(),
compute_clusterdepth(),
compute_clustermass(),
compute_maxT(),
compute_minP(),
compute_stepdownmaxT(),
compute_troendle()