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# Generate typical data found inside the function mmc()
S0 <- 0
y <- rnorm(100)
statistic <- function(y, v) mean(y) * v
dgp <- function(y, v) sample(y, replace = TRUE)
est <- 1
lower <- -1
upper <- 1
N <- 99
type <- "geq"
method <- "GenSA"
alpha <- 0.05
control <- MaxMC:::get_control(method)
call <- call("mc",y= y, statistic = statistic, dgp = dgp, N = 99, type = type)
seed <- NULL
lmc <- list(pval = 0.10)
pval <- 0.65
opt_result <- list(value = 0.10)
opt_trace <- as.data.frame(matrix(data = NA, control$maxit, 3,
dimnames = list(NULL,c("ite","pval","max"))))
# Combine data and return it as an object of class 'mmc'
MaxMC:::return_mmc(S0 = S0, y = y, statistic = statistic, dgp = dgp, est = est, lower = lower,
upper = upper, N = N, type = type, method = method, alpha = alpha,
control = control, call = call, seed = seed, lmc = lmc,
opt_result = opt_result, opt_trace = opt_trace)
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