Nothing
context("Single Dichotomous Models MCMC")
test_that("Probit", {
set.seed(5981)
mData <- build_single_dichotomous_dataset()
c = single_dichotomous_fit(mData[,1],mData[,2],mData[,3],model_type = "probit", fit_type = "mcmc")
validate_model(c, "Model: Probit" , c(-1.22897249357605, 0.946667348047251) , c(BMD = 13.7570231637969, BMDL = 11.0421600688424, BMDU = 17.634673852233) )
})
test_that("Log Probit", {
set.seed(5981)
mData <- build_single_dichotomous_dataset2()
c = single_dichotomous_fit(mData[,1],mData[,2],mData[,3],model_type = "log-probit", fit_type = "mcmc")
validate_model(c, "Model: Log-Probit" , c(-2.5767039674999, -0.363921570939808, 0.585986511476555) , c(BMD = 11.5294629371935, BMDL = 3.54819293851276, BMDU = 21.0396223458889) )
})
test_that("Weibull", {
set.seed(5981)
mData <- build_single_dichotomous_dataset()
c = single_dichotomous_fit(mData[,1],mData[,2],mData[,3],model_type = "weibull", fit_type = "mcmc")
validate_model(c, "Model: Weibull" , c(-2.86014800998383, 0.661116573139896, 0.438604630748536) , c(BMD = 5.1170096470376, BMDL = 1.46662721211377, BMDU = 11.8009898041251) )
})
test_that("Plots", {
set.seed(5981)
mData <- build_single_dichotomous_dataset()
c = single_dichotomous_fit(mData[,1],mData[,2],mData[,3],model_type = "weibull", fit_type = "mcmc")
mcmc_plot <- plot(c)
expect_identical(mcmc_plot$labels$x, "Dose")
expect_identical(mcmc_plot$labels$y, "Proportion")
#TODO should the title have the distribution name?
expect_identical(mcmc_plot$labels$title, "Model: Weibull")
c = single_dichotomous_fit(mData[,1],mData[,2],mData[,3],model_type = "hill", fit_type = "mcmc")
mcmc_plot <- plot(c)
expect_identical(mcmc_plot$labels$x, "Dose")
expect_identical(mcmc_plot$labels$y, "Proportion")
#TODO should the title have the distribution name?
expect_identical(mcmc_plot$labels$title, "Model: Hill")
})
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