fuzzyBHexact {fuzzyFDR} | R Documentation |
Exact calculation of fuzzy decision rules for multiple testing. Controls the FDR (false discovery rate) using the Benjamini and Hochberg method.
fuzzyBHexact(pvals, pprev, alpha = 0.05, tol = 1e-05, q.myuni = T, dp = 20)
pvals |
observed discrete p-values |
pprev |
previously attainable p-values under the null distribution |
alpha |
significance level of the FDR procedure |
tol |
tolerance for my.match and my.unique |
q.myuni |
logical. Use my.match instead of match? |
dp |
no. decimal places to round p-values to |
my.match and my.unique may be used instead of match and unique if there is a problem with calculating the unique set of p-values (sometimes a problem with very small p-values)
Data frame containing the p-values and previously attainable p-values input to the function, and the tau (fuzzy decision rule) output. Also contains the minimum and maximum ranks over allocations for each p-value.
Alex Lewin
Kulinsakaya and Lewin (2007).
data(example1) names(example1) fuzzyBHexact(example1$pvals,example1$pprev,alpha=0.05) data(example2) names(example2) fuzzyBHexact(example2$pvals,example2$pprev,alpha=0.05)