reg_simulation2 {MSIMST} | R Documentation |
The Function for the Simulation Study with the Variable Selection
Description
This simulation study is designed to demonstrate that using the grouped horseshoe prior can successfully separate signals from noise.
Usage
reg_simulation2(N, ni_lambda, beta, beta_b, dsq, sigmasq, delta, nu)
Arguments
N |
The number of subjects. |
ni_lambda |
The mean of Poisson distribution. |
beta |
The covariates' coefficients. A 10 by 1 vector. |
beta_b |
The slope of PD response. |
dsq |
A part of covariance parameter. |
sigmasq |
A part of covariance parameter. |
delta |
The skewness parameter. |
nu |
The degree of freedom. |
Details
More details of the design of this simulation study can be found in the vignette. Users can access the vignette by the command vignette(package = "MSIMST")
.
Value
A simulated dataset with the response variable y
and the design matrix X
.
Examples
set.seed(200)
simulated_data <- reg_simulation2(N = 50,
ni_lambda = 8,
beta = c(rep(1,6),rep(0,4)),
beta_b = 1.5,
dsq = 0.1,
sigmasq = 0.5,
delta = 0.6,
nu = 5.89)
y <- simulated_data$y
X <- simulated_data$X
[Package MSIMST version 1.1 Index]