The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

bayefdr

The goal of bayefdr is to provide tools for the estimation and optimisation of Bayesian expected false discovery and expected false negative rates.

Installation

You can install the released version of bayefdr from CRAN with:

install.packages("bayefdr")
# development version:
## devtools::install_github("VallejosGroup/bayefdr")

Usage

The main functions in this package are efdr, efnr and efdr_search. efdr and efnr calculate the EFDR or EFNR for a vector of probabilities given a specified probability threshold. efdr_search finds the probability threshold that matches a target EFDR as closely as possible. The basic input to this function is a vector of probabilities and a target EFDR.

library("bayefdr")
set.seed(42)
probs <- runif(100)
efdr(0.7, probs)
#> [1] 0.1429126
efnr(0.7, probs)
#> [1] 0.3531349
efdr <- efdr_search(probs, target_efdr = 0.1)
efdr
#> An object of class 'bayefdr'.
#>  Optimal threshold: 0.768 EFDR: 0.0985 EFNR: 0.399

The output of this function is a data.frame with some extra attributes. There is a plot method too.

head(efdr)
#>   threshold     EFDR      EFNR
#> 1   0.50000 0.239581 0.2361073
#> 2   0.50025 0.239581 0.2361073
#> 3   0.50050 0.239581 0.2361073
#> 4   0.50075 0.239581 0.2361073
#> 5   0.50100 0.239581 0.2361073
#> 6   0.50125 0.239581 0.2361073
plot(efdr)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.