HomUHet.sim: simulate multiple data sets with both homogeneous and...

In Pei-Yang/HomUHet: Identifying and Separating Homogeneous and Heterogeneous Predictors

Description

this function simulate data

Usage

HomUHet.sim(
  age = TRUE,
  sex = TRUE,
  n_homo,
  n_heter,
  K,
  n_cont,
  n_SNP,
  rho = 0.5,
  sigma = 2,
  nlower = 50,
  nupper = 300,
  beta = NULL
)

Arguments

age	TRUE if covariate age should be included. simulated from N (40, 5)
sex	TRUE if covariate sex should be included. simulated from Bernoulli (p), where p is a random number between 0 and 1.
n_homo	number of homogeneous coefficients.
n_heter	number of heterogeneous coefficients.
n_cont	the number of continuous predictors. 0 if there will be no continuous predictors
n_SNP	the number of SNP predictors. 0 if there will be no SNP predictors
rho	a number between 0 and 1. controlling the degree of correlation between predictors
sigma	a positive number. controlling the added noise to the simulated response variable
nlower	the lower bound of the K sample sizes
nupper	the upper bound of the K sample sizes
beta	if the users wish to supply the coefficients on their own, enter a coefficient matrix where the columns containing the K coefficients of each predictor, for all genetic and non-genetic predictors.

Value

the simulated data

data	the simulated data
beta	the simulated beta matrix
homo_index	the column numbers of homogeneous coefficients
heter_index	the column numbers of heterogeneous coefficients

Pei-Yang/HomUHet documentation built on Dec. 18, 2021, 6:46 a.m.