context("mice.impute.lasso.norm")
#########################
# TEST 1: Simple problem #
#########################
set.seed(123)
# generate data
n <- 1e3
y <- rnorm(n)
x <- y * .3 + rnorm(n, 0, .25)
x2 <- x + rnorm(n, 2, 3)
x <- cbind(x, x2)
# make missingness
y[sample(1:n, n * .3)] <- NA
ry <- !is.na(y)
# Use univariate imputation model
set.seed(123)
imps <- mice.impute.lasso.norm(y, ry, x)
test_that("Returns requested length", {
expect_equal(length(imps), sum(!ry))
})
#########################
# TEST 2: Use it within mice call #
#########################
boys_cont <- boys[, 1:4]
durr_default <- mice(boys_cont,
m = 2, maxit = 2, method = "lasso.norm",
print = FALSE
)
durr_custom <- mice(boys_cont,
m = 2, maxit = 2, method = "lasso.norm",
nfolds = 5,
print = FALSE
)
test_that("mice call works", {
expect_equal(class(durr_custom), "mids")
})
test_that("mice call works w/ custom arguments", {
expect_equal(class(durr_custom), "mids")
})
#########################
# TEST 3: Failure because removals by remove.lindep() #577
#########################
# library(mice, warn.conflicts = FALSE)
# set.seed(123)
#
# n <- 100
# y <- rnorm(n)
# x <- rep(1, n)
# y[sample(1:n, n * .3)] <- NA
# ry <- !is.na(y)
#
# # Test univariate imputation outside mice
# imps <- mice.impute.lasso.norm(y, ry, as.matrix(x))
# imps <- mice.impute.lasso.norm(y, ry, as.matrix(x)[, -1])
#
# # Test inside mice
# input <- data.frame(y = y, x = 1)
# imp <- mice(input, m = 1, maxit = 1, method = "lasso.norm", print = FALSE)
# imp <- mice(input, m = 1, maxit = 1, method = "lasso.norm", print = FALSE, eps = 0)
# imp <- mice(input, m = 1, maxit = 1, method = "lasso.norm", print = FALSE, eps = 0, remove.constant = FALSE)
#
# test_that("skip remove.lindep()", {
# expect_silent(mice(data, m = 1, maxit = 1, method = "lasso.norm", eps = 0, print = FALSE))
# })
#
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