reg_simulation2 {MSIMST} | R Documentation |
This simulation study is designed to demonstrate that using the grouped horseshoe prior can successfully separate signals from noise.
reg_simulation2(N, ni_lambda, beta, beta_b, dsq, sigmasq, delta, nu)
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. |
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")
.
A simulated dataset with the response variable y
and the design matrix X
.
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