MSIMST (version 1.1)

reg_simulation2: 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)

Value

A simulated dataset with the response variable y and the design matrix X.

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").

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