library(rstan)
rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores())
library(gmo)
data <- list(J = 8,
K = 2,
y = c(28, 8, -3, 7, -1, 1, 18, 12),
sigma = c(15, 10, 16, 11, 9, 11, 10, 18))
local_file <- "models/8schools_local.stan"
M <- 2
m <- 1
draws <- 10
phi <- c(2,5)
seed <- 42
alpha <- "random"
# Check conditional approximation.
g_alpha <- sampling(stan_model(local_file),
data=c(data, list(phi=phi)),
iter=2*M*draws, chains=1,
seed=seed, init=alpha)
# Check extraction of samples.
J <- data$J
alpha_sims <- extract(g_alpha, permuted=FALSE)[(m-1)*draws + 1:draws,,1:J]
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