Nothing
context("Finite sample corrections")
set.seed(1)
n <- 30
mu <- 5
sigma <- 2
dt <- data.frame(Y = rnorm(n, mean = mu, sd = sigma), id = 1:n)
test_eefun <- function(data){
function(theta){
with(data,
c(Y - theta[1],
(Y - theta[1])^2 - theta[2] )
)
}
}
rooter <- new('root_control', .options = list(start = c(1, 1)))
bias_estimates <- m_estimate(
estFUN = test_eefun,
data = dt,
units = 'id',
root_control = rooter,
corrections = list(test = correction(fay_bias_correction,
b = 0.75)))
df1_estimates <- m_estimate(
estFUN = test_eefun,
data = dt,
units = 'id',
root_control = rooter,
corrections = list(test = correction(FUN = fay_df_correction,
b = 0.75, L = c(1, 1), version = 1)))
df2_estimates <- m_estimate(
estFUN = test_eefun,
data = dt,
units = 'id',
root_control = rooter,
corrections = list(test = correction(fay_df_correction,
b = 0.75, L = c(1, 1), version = 2)))
test_that("Bias correction returns matrix", {
expect_is(bias_estimates@corrections$test, 'matrix')
})
test_that("DF1 correction returns a scalar", {
expect_is(df1_estimates@corrections$test, 'numeric')
expect_equal(length(df1_estimates@corrections$test), 1)
})
test_that("DF2 correction returns a scalar", {
expect_is(df2_estimates@corrections$test, 'numeric')
expect_equal(length(df2_estimates@corrections$test), 1)
})
test_that("get_corrections() accessor returns list", {
expect_is(get_corrections(bias_estimates), 'list')
})
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