##############################################################################

# Subbolafit
# checks against original implementation of subbotools
# Depends on using the same sample to fit as the subbotools package
# since R changes the rng in each version, to work this test must be manually
# updated each time or use a constant sample
skip()
paste0("Subbolafit")

# this routine does not output the std error for the parameters, neither does
# it returns the covariance matrix

test_that("SubLaplace:", {
  # subbolafit -V 1 < sublaplace.txt
  # bl           br           a            m            log-likelihood
  # 4.989886e-01 4.996535e-01 3.995011e+00 -2.153289e-05 3.385670e+00

  orig_value <-
    generate_orig_dt(
      coef = c(4.989886e-01, 4.996535e-01, 3.995011e+00, -2.153289e-05),
      log_likelihood = 3.385670e+00,
      distribution = "subbolafit"
    )
  check_fits(orig_value, .5, subbolafit)
})

test_that("Laplace:", {
  # subbolafit -V 1 < laplace.txt
  # bl           br           a            m            log-likelihood
  # 1.000817e+00 1.002628e+00 1.999673e+00 3.943432e-04 2.385405e+00

  orig_value <-
    generate_orig_dt(
      coef = c(1.000817e+00, 1.002628e+00, 1.999673e+00, 3.943432e-04),
      log_likelihood = 2.385405e+00,
      distribution = "subbolafit"
    )
  check_fits(orig_value, 1, subbolafit)
})

test_that("Subnormal:", {
  # subbolafit -V 1 < subnormal.txt
  # bl           br           a             m            log-likelihood
  # 1.502682e+00 1.505530e+00 7.637474e-01 -3.984272e-04 1.257220e+00

  orig_value <-
    generate_orig_dt(
      coef = c(1.502682e+00, 1.505530e+00, 7.637474e-01, -3.984272e-04),
      log_likelihood = 1.257220e+00,
      distribution = "subbolafit"
    )

  check_fits(orig_value, 1.5, subbolafit)
})


test_that("Normal:", {
  # subbolafit -V 1 < normal.txt
  # bl           br           a            m            log-likelihood
  # 2.004459e+00 2.004388e+00 1.415614e+00 6.393844e-05 1.765696e+00

  orig_value <-
    generate_orig_dt(
      coef = c(2.004393e+00, 2.004388e+00, 1.415614e+00, 6.393844e-05),
      log_likelihood = 1.765696e+00
    )

  check_fits(orig_value, 2, subbolafit)
})

test_that("SuperNormal:", {
  # subbolafit -V 1 < supernormal.txt
  # bl           br           a            m            log-likelihood
  # 2.495521e+00 2.502094e+00 1.385714e+00 -2.454156e-04 1.666428e+00

  orig_value <-
    generate_orig_dt(
      coef = c(2.495521e+00, 2.502094e+00, 1.385714e+00, -2.454156e-04),
      log_likelihood = 1.666428e+00,
      distribution = "subbolafit"
    )
  check_fits(orig_value, 2.5, subbolafit)
})

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