# S3methods tests
# test simulate
# set.seed(123)
# source_nonprob_p <- read.csv("test1_nonprob.csv")
# sample_a <- read.csv("test1_prob.csv")
# svy_a <- svydesign(ids= ~1, weights = ~ w_a, data = sample_a)
#
# test1a <- nonprob(selection = ~ x,
#                   target = ~ y1,
#                   data = source_nonprob_p,
#                   method_selection = "logit",
#                   svydesign = svy_a)
#
# expect_silent(
#   summary(test1a)
# )
#
# expect_silent(
#   nobs(test1a)
# )
#
# expect_silent(
#   pop.size(test1a)
# )
#
# expect_silent(
#   residuals(test1a)
# )
#
# expect_silent(
#   residuals(test1a, type = "pearson")
# )
#
# expect_silent(
#   residuals(test1a, type = "working")
# )
#
# expect_silent(
#   residuals(test1a, type = "deviance")
# )
#
# expect_silent(
#   residuals(test1a, "pearsonSTD")
# )

# expect_silent(
#   cooks.distance(test1a)
# )
#
# expect_silent(
#   hatvalues(test1a)
# )

# expect_silent(
#   logLik(test1a)
# )
#
# expect_silent(
#   AIC(test1a)
# )
#
# expect_silent(
#   BIC(test1a)
# )
#
# expect_silent(
#   confint(test1a)
# )
#
# expect_silent(
#   vcov(test1a)
# )
#
# expect_silent(
#   deviance(test1a)
# )

# test2a <- nonprob(outcome = y1 ~ x,
#                   data = source_nonprob_p,
#                   method_selection = "logit",
#                   svydesign = svy_a)
# expect_silent(
#   summary(test2a)
# )
#
# expect_silent(
#   nobs(test2a)
# )
#
# expect_silent(
#   pop.size(test2a)
# )
#
# expect_silent(
#   residuals(test2a)
# )
#
# expect_silent(
#   residuals(test2a, type = "pearson")
# )
#
# expect_silent(
#   residuals(test2a, type = "working")
# )

# expect_silent(
#   residuals(test2a, type = "deviance")
# )
#
# expect_silent(
#   residuals(test2a, "pearsonSTD")
# )

# if (isTRUE(tolower(Sys.getenv("TEST_NONPROBSVY_MULTICORE_DEVELOPER")) == "true")) {
#   expect_silent(
#     cooks.distance(test2a)
#   )
#   expect_silent(
#     hatvalues(test2a)
#   )
# }

# expect_silent(
#   logLik(test2a)
# )
#
# expect_silent(
#   AIC(test2a)
# )
#
# expect_silent(
#   BIC(test2a)
# )
#
# expect_silent(
#   confint(test2a)
# )
#
# expect_silent(
#   vcov(test2a)
# )
#
# expect_silent(
#   deviance(test2a)
# )
#
# test3a <- nonprob(outcome = y1 ~ x,
#                   selection = ~ x,
#                   data = source_nonprob_p,
#                   method_selection = "logit",
#                   svydesign = svy_a)
# expect_silent(
#   summary(test3a)
# )
#
# expect_silent(
#   nobs(test3a)
# )
#
# expect_silent(
#   pop.size(test3a)
# )
#
# expect_silent(
#   residuals(test3a)
# )
#
# expect_silent(
#   residuals(test3a, type = "pearson")
# )
#
# expect_silent(
#   residuals(test3a, type = "working")
# )
#
# expect_silent(
#   residuals(test3a, type = "deviance")
# )
#
# expect_silent(
#   residuals(test3a, "pearsonSTD")
# )

# if (isTRUE(tolower(Sys.getenv("TEST_NONPROBSVY_MULTICORE_DEVELOPER")) == "true")) {
#   expect_silent(
#     cooks.distance(test3a)
#   )
#
#   expect_silent(
#     hatvalues(test3a)
#   )
# }

# expect_silent(
#   logLik(test3a)
# )
#
# expect_silent(
#   AIC(test3a)
# )
#
# expect_silent(
#   BIC(test3a)
# )
#
# expect_silent(
#   confint(test3a)
# )
#
# expect_silent(
#   vcov(test3a)
# )
#
# expect_silent(
#   deviance(test3a)
# )
