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## @knitr models
make_normal_model <- function(theta_norm, p) {
new_model(name = "norm",
label = sprintf("p = %s, theta_norm = %s", p, theta_norm),
params = list(theta_norm = theta_norm, p = p,
theta = c(theta_norm, rep(0, p - 1))),
simulate = function(theta, p, nsim) {
Y <- theta + matrix(rnorm(nsim * p), p, nsim)
return(split(Y, col(Y))) # make each col its own list element
})
}
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