randomFSSEMdata4Cor: randomFSSEMdata4Cor

In fssemR: Fused Sparse Structural Equation Models to Jointly Infer Gene Regulatory Network

randomFSSEMdata4Cor

Description

randomFSSEMdata4Cor

Usage

randomFSSEMdata4Cor(
  n,
  p,
  k,
  sparse = 0.1,
  df = 0.2,
  sigma2 = 0.01,
  u = 5,
  type = c("DG", "ER"),
  dag = TRUE,
  coef = c(0.2, 0.4),
  nhub = 2,
  r = 0.5
)

Arguments

n	number of observations. Vector for unbalance observations
p	number of genes
k	number of eQTLs
sparse	ratio of edges / gene_number
df	ratio of differential edges among two network
sigma2	noise variance of error
u	variance of bias in SEM model.
type	type of generated network, can be selected as DG, ER, Scale-free network
dag	network is directed-acyclic or not. Default TRUE
coef	Range of absolute value of coefficients in simulated network matrices. Default (0.2, 0.4), or (0.5, 1)
nhub	If you select to generate ER network, nhub is the number of pre-defined hub node number. Default 2
r	correlation between different observations

Value

list of generated data

Data

List of observed, Xs, Ys, Sk

Vars

List of model, Bs, Fs, mu, n, p, k

fssemR documentation built on March 18, 2022, 7:24 p.m.