Dear R experts,
I am trying to create a dataset, with one dependent binomial and one
independen (normal) variable.
I have the condition that my x should be created in the following way:
if y=0 my x should have mean=0.2 and variance=1
if y=1 my x should have mean=0.7 and variance=1
Furthermore, my y is chosen with a prbability of 0.5
I tried it with the following expression:
n <- 1
prob <- 0.5
result.y <- vector("list",100)
result.X <- vector("list",100)
for (i in 1:100)
{
y <- rbern(n, prob)
X <- if(y==0){X <- rnorm(n, mean=0.2, sd=1)}else{X <- mvrnorm(n, mean=0.7,
sd=1)}
result.y[[i]] <- y
result.X[[i]] <- X
}
y <- result.y
X <- result.X
matrix <- cbind(result.y, result.X)
View(matrix)
However, when I try to run a logistic regression
glm.out = glm(formula = y ~ X, family = binomial(logit))
summary(glm.out)
hat.beta.L <- coef(glm.out)
I get the error massage
Fehler in model.frame.default(formula = y ~ X, drop.unused.levels = TRUE) :
ungültiger Typ (list) für die Variable 'y'
Does someone know what I am doing wrong?
Thank you very much for your help, I really appreciate it.
--
View this message in context:
http://r.789695.n4.nabble.com/creating-multivariate-normal-random-variables-tp4666678.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
