adaptive.bh: function to do ...
In mcp.project: Applies different False Discovery Rate controlling procedures

Description Usage Arguments Details Value Note Author(s) References See Also Examples

~~ A concise (1-5 lines) description of what the function does. ~~

1	adaptive.bh(sorted, q, m)

`sorted`	~~Describe `sorted` here~~
`q`	~~Describe `q` here~~
`m`	~~Describe `m` here~~

~~ If necessary, more details than the description above ~~

~Describe the value returned If it is a LIST, use

`comp1`	Description of 'comp1'
`comp2`	Description of 'comp2'

...

~~further notes~~

~Make other sections like Warning with Warning .... ~

~~who you are~~

~put references to the literature/web site here ~

~~objects to See Also as help, ~~~

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--    or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (sorted, q, m) 
{
    cat("Calling Adaptive BH \n")
    flush.console
    stage.one = bh(sorted, q, adjust = T, m = m)
    r = sum(stage.one$Pvals[["rejected"]])
    if (r == 0) 
        return(stage.one)
    else m0 = bh.m0.estimate(sorted = sorted, m = m)
    output = bh(sorted = sorted, q = q, m0 = m0, m = m)
    output$Pvals[["adjusted.pvals"]] = bh.adjust(sorted, m = m, 
        m0 = m0)
    return(output)
  }