nempibs: Bootstrapping function

Description Usage Arguments Value Author(s) Examples

View source: R/nempi_main.r

Description

Bootstrap algorithm to get a more stable result.

Usage

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nempibs(D, bsruns = 100, bssize = 0.5, replace = TRUE, ...)

Arguments

D

either a binary effects matrix or log odds matrix as

bsruns

number of bootstraps

bssize

number of E-genes for each boostrap

replace

if TRUE, actual bootstrap, if False sub-sampling

...

additional parameters for the function nempi

Value

list with aggregate Gamma and aggregate causal network phi

Author(s)

Martin Pirkl

Examples

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D <- matrix(rnorm(1000*100), 1000, 100)
colnames(D) <- sample(seq_len(5), 100, replace = TRUE)
Gamma <- matrix(sample(c(0,1), 5*100, replace = TRUE, p = c(0.9, 0.1)), 5,
100)
Gamma <- apply(Gamma, 2, function(x) return(x/sum(x)))
Gamma[is.na(Gamma)] <- 0
rownames(Gamma) <- seq_len(5)
result <- nempibs(D, bsruns = 3, Gamma = Gamma)

cbg-ethz/nempi documentation built on May 4, 2021, 9:44 a.m.