glm.generator {ELCIC} | R Documentation |
Cross-sectional data generation under GLM
Description
A function provides simulated outcomes as well as covariates under the framework of GLM. All covariates (except for intercept) are normally distributed.
Usage
glm.generator(beta, samplesize, rho = 0, dist, sd.gaussian = NULL, ov = NULL)
Arguments
beta |
The underlying true coefficient for each covariates in the model (including the intercept). |
samplesize |
The sample size. |
rho |
The correlation coefficient among covariates. |
dist |
A specified distribution. It can be "gaussian", "poisson",and "binomial". |
sd.gaussian |
The standard deviation for the outcome from Gaussian distribution. |
ov |
The dispersion parameter for the outcome from Negative Binomial distribution. |
Value
x: a matrix containing continuous covariates. The first column should contain all ones corresponding to the intercept.
y: a vector containing outcomes.
Examples
beta<-c(0.5,0.5,0.5,0)
samplesize<-100
data<-glm.generator(beta=beta,samplesize=samplesize,rho=0.5,dist="poisson")
[Package ELCIC version 0.2.1 Index]