lfdr.empiricalNull: Histogram-based estimator (HBE).

Description

Wrapper of Efrons LFDR (here called Histogram-based estimator (HBE)) with empirical estimation of the null hypothesis distribution (HBEE): lfdr.empiricalNull (nulltype=1 by default) or with assumed theoretical null hypothesis distribution as N(0,1) (HBEA): lfdr.assumedNull.

Usage

lfdr.assumedNull(stat= NULL, pvalue = NULL, bre = 120, df = 7, plot = 0, ...)
lfdr.empiricalNull(stat= NULL, pvalue = NULL, nulltype = 1, bre = 120, df = 7, plot = 0, ...)

Arguments

stat

Input numeric vector of statistics. At least one of the inputs (pvalue or stat) must be non null.

pvalue

Optional input numeric vector of p-values. At least one of the inputs (pvalue or stat) must be non null. If the non empty input is a vector of p-values, the function qnorm is applied to it (see manual of package locfdr).

nulltype

Parameter for selection of the type of null hypothesis distribution in Efrons method. The value nulltype = 1 is the default in lfdr.elfdr (See function locfdr in locfdr package).

bre

Number of breaks in the discretization of the z-score axis in Efrons method (see package locfdr). Useful when the number of features is small.

Degrees of freedom for fitting the estimated density $f(z)$ in Efrons method (see package locfdr). Useful when the number of features is small.

plot

Optional. If plot = 0, no plots are made (see package locfdr).

...

Further arguments to pass to function locfdr to compute HBEE (see locfdr R package).

Value

LFDR.hat: Vector of estimates of the HBE.
p0.hat: Estimated proportion of affected features p0 (null hypothesis).
stat: Input vector of statistics.
info: Method name and information about computation failure.

References

Efron, B., Turnbull, B. B., & Narasimhan, B. (2011). locfdr: Computes local false discovery rates. Retrieved from http://cran.r-project.org/src/contrib/Archive/locfdr/

Examples

Run this code

# a statistic vector with missing elements
ss <- runif(55,-1,5) ;ss[c(13,2,5)]<-NA
# a p-values vector with missing elements
pp <- runif(55) ;pp[c(13,2,5)]<-NA

z1 <- lfdr.assumedNull(stat = ss, df = 3)
z2 <- lfdr.empiricalNull(pvalue = pp, df=3)