skip_if_not_installed("estimatr")

m1 <- estimatr::iv_robust(mpg ~ gear + cyl | carb + wt, data = mtcars)

test_that("model_info", {
  expect_true(model_info(m1)$is_linear)
})

test_that("find_predictors", {
  expect_identical(
    find_predictors(m1),
    list(
      conditional = c("gear", "cyl"),
      instruments = c("carb", "wt")
    )
  )
  expect_identical(
    find_predictors(m1, component = "instruments"),
    list(instruments = c("carb", "wt"))
  )
  expect_identical(
    find_predictors(m1, flatten = TRUE),
    c("gear", "cyl", "carb", "wt")
  )
  expect_null(find_predictors(m1, effects = "random"))
})

test_that("find_random", {
  expect_null(find_random(m1))
})

test_that("get_random", {
  expect_warning(get_random(m1))
})

test_that("find_response", {
  expect_identical(find_response(m1), "mpg")
})

test_that("get_response", {
  expect_equal(get_response(m1), mtcars$mpg)
})

test_that("get_predictors", {
  expect_equal(colnames(get_predictors(m1)), c("gear", "cyl", "carb", "wt"))
})

test_that("get_data", {
  expect_equal(nrow(get_data(m1)), 32)
  expect_equal(
    colnames(get_data(m1)),
    c("mpg", "gear", "cyl", "carb", "wt")
  )
})

test_that("find_formula", {
  expect_length(find_formula(m1), 2)
  expect_equal(
    find_formula(m1),
    list(
      conditional = as.formula("mpg ~ gear + cyl"),
      instruments = as.formula("~carb + wt")
    ),
    ignore_attr = TRUE
  )
})

test_that("find_terms", {
  expect_equal(
    find_terms(m1),
    list(
      response = "mpg",
      conditional = c("gear", "cyl"),
      instruments = c("carb", "wt")
    )
  )
  expect_equal(
    find_terms(m1, flatten = TRUE),
    c("mpg", "gear", "cyl", "carb", "wt")
  )
})

test_that("n_obs", {
  expect_equal(n_obs(m1), 32)
})

test_that("link_function", {
  expect_equal(link_function(m1)(0.2), 0.2, tolerance = 1e-5)
})

test_that("link_inverse", {
  expect_equal(link_inverse(m1)(0.2), 0.2, tolerance = 1e-5)
})

test_that("find_parameters", {
  expect_equal(
    find_parameters(m1),
    list(conditional = c("(Intercept)", "gear", "cyl"))
  )
  expect_equal(nrow(get_parameters(m1)), 3)
  expect_equal(
    get_parameters(m1)$Parameter,
    c("(Intercept)", "gear", "cyl")
  )
})

test_that("is_multivariate", {
  expect_false(is_multivariate(m1))
})

test_that("find_algorithm", {
  expect_warning(expect_null(find_algorithm(m1)))
})

test_that("find_statistic", {
  expect_identical(find_statistic(m1), "t-statistic")
})

skip_if_not_installed("ivreg")
data("CigaretteDemand", package = "ivreg")
m2 <- estimatr::iv_robust(
  log(packs) ~ log(rprice) + log(rincome) | salestax + log(rincome),
  data = CigaretteDemand
)
m3 <- estimatr::iv_robust(
  packs ~ log(rprice) + log(rincome) | salestax + log(rincome),
  data = CigaretteDemand
)

m4 <- estimatr::lm_robust(
  log(packs) ~ log(rprice) + log(rincome) | salestax + log(rincome),
  data = CigaretteDemand
)
m5 <- estimatr::lm_robust(
  packs ~ log(rprice) + log(rincome) | salestax + log(rincome),
  data = CigaretteDemand
)

test_that("get_loglikelihood", {
  expect_equal(as.numeric(get_loglikelihood(m2)), -286.56173, tolerance = 1e-3)
  expect_equal(as.numeric(get_loglikelihood(m3)), -206.39546, tolerance = 1e-3)
  expect_equal(as.numeric(get_loglikelihood(m4)), -286.55949, tolerance = 1e-3)
  expect_equal(as.numeric(get_loglikelihood(m5)), -205.63306, tolerance = 1e-3)
})