R 为什么随机效应估计器不正确
我试图用二项式数据模拟glmmLasso 但随机效应估计器和我给出的5不一样 我的代码有问题吗 如果不是,为什么会出现这样的随机效应R 为什么随机效应估计器不正确,r,mixed-models,R,Mixed Models,我试图用二项式数据模拟glmmLasso 但随机效应估计器和我给出的5不一样 我的代码有问题吗 如果不是,为什么会出现这样的随机效应 makedata <- function(I, J, p, sigmaB){ N <- I*J # fixed effect generation beta0 <- runif(1, 0, 1) beta <- sort(runif(p, 0, 1)) # x generation x <- matrix(ru
makedata <- function(I, J, p, sigmaB){
N <- I*J
# fixed effect generation
beta0 <- runif(1, 0, 1)
beta <- sort(runif(p, 0, 1))
# x generation
x <- matrix(runif(N*p, -1, 1), N, p)
# random effect generation
b0 <- rep(rnorm(I, 0, sigmaB), each=J)
# group
group <- as.factor(rep(1:I, each = J))
# y generation
k <- exp(-(beta0 + x %*% beta + b0))
y <- rbinom(n = length(k), size = 1, prob = (1/(1+k)))
#standardization
sx <- scale(x, center = TRUE, scale = TRUE)
simuldata <- data.frame(y = y, x = sx, group)
res <- list(simuldata=simuldata)
return(res)
}
# I : number of groups
I <- 20
# J : number of observation in group
J <- 10
# p : number of variables
p <- 20
# sigmaB : sd of random effect b0
sigmaB <- 5
set.seed(231233)
simdata <- makedata(I, J, p, sigmaB)
lam <- 10
xnam <- paste("x", 1:p, sep=".")
fmla <- as.formula(paste("y ~ ", paste(xnam, collapse= "+")))
glmm <- glmmLasso(fmla, rnd = list(group=~1), data = simdata, lambda = lam, control = list(scale = T, center = T))
summary(glmm)
makedata