FDRCurve | R Documentation |
Estimates the expected proportion of misclassified units when using a given r-value threshold. If plot=TRUE, the curve is plotted before the estimated function is returned.
FDRCurve(object, q, threshold = 1, plot = TRUE, xlim, ylim, xlab, ylab, main, ...)
object |
An object of class "rvals" |
q |
A value in between 0 and 1; the desired level of FDR control. |
threshold |
The r-value threshold. |
plot |
logical; if TRUE, the estimated FDR curve is plotted. |
xlim,ylim |
x and y - axis limits for the plot |
xlab,ylab |
x and y - axis labels |
main |
the title of the plot |
... |
additional arguments to |
Consider parameters of interest (θ_1,...,θ_n) with an effect of size of interest τ. That is, a unit is taken to be "null" if θ_i ≤ τ and taken to be "non-null" if θ_i > τ.
For r-values r_1,...,r_n and a procedure which "rejects" units satisfying r_i ≤ c, the FDR is defined to be
FDR(c) = P(θ_i < τ,r_i ≤ c)/P(r_i ≤ c).
FDRCurve
estimates FDR(c)
for values of c across (0,1) and plots (if plot=TRUE
)
the resulting curve.
A list with the following two components
fdrcurve |
A function which returns the estimated FDR for each r-value threshold. |
Rval.cut |
The largest r-value cutoff which still gives an estimated FDR less than q. |
Nicholas Henderson and Michael Newton
OverlapCurve
n <- 500 theta <- rnorm(n) ses <- sqrt(rgamma(n,shape=1,scale=1)) XX <- theta + ses*rnorm(n) dd <- cbind(XX,ses) rvs <- rvalues(dd, family = gaussian) FDRCurve(rvs, q = .1, threshold = .3, cex.main = 1.5)
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