BiG (version 0.1.0)

sim_lvm: Simulate rank data from latent variable model

Description

Simulate rank data from latent variable model

Usage

sim_lvm(G, S, n_p1, rho, p_p1, p_p2, lambda, n_T)

Arguments

G

total number of genes involved in all of the studies.

S

number of studies (ranked lists) to be aggregated.

n_p1

number of studies belong to platform 1.

rho

correlation between local importance (w) and global importance (mu) for each study, which determines the total variance of w.

p_p1, p_p2

percentage of total variance of w contributed by platform variance from platform 1 and platform 2 respectively for the study with the lowest total variance.

lambda

inclusion rate for each study.

n_T

vector of length S that contains number of top ranked items in each study.

Examples

# NOT RUN {
set.seed(1234)
sim_lvm(G=25, S=6, n_p1=3, rho=runif(6,min=0.3,max=0.9), p_p1=0.6, p_p2=0.8, 
        lambda=runif(6,min=0.6,max=0.8), n_T=sample(c(5,10,15),6,replace=TRUE))
# }