two.stage: 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

Utility function for the "fdr" function in package mcp.project.

1	two.stage(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 two.stage \n")
    flush.console
    q1 = q/(1 + q)
    stage.one = bh(sorted, q1, adjust = T, m = m)
    r = sum(stage.one$Pvals[["rejected"]])
    if (r == 0) {
        stage.one$Pvals[["adjusted.pvals"]] = 1
        return(stage.one)
    }
    else if (r == m) {
        stage.one$Pvals[["adjusted.pvals"]] = stage.one$Pvals[["adjusted.pvals"]][1]
        return(stage.one)
    }
    else {
        m0 = m - r
        output = bh(sorted = sorted, q = q1, m0 = m0, m = m)
        output$Pvals[["adjusted.pvals"]] = two.stage.adjust(sorted, 
            q)
        return(output)
    }
  }