Nothing
test_that("test fit and post fit utilities", {
fit <- readRDS("fit.RDS")
sampler_params <- rstan::get_sampler_params(fit$stanfit, inc_warmup = FALSE)
samplesN <- dim(sampler_params[[1]])[1] * length(sampler_params)
# check that the fit itself is what we think it is
expect_s3_class(fit, "cumhist")
# checking that extraction methods work
expect_s3_class(bayes_R2(fit), "data.frame")
# history term
expect_s3_class(bistablehistory::historyef(fit), "data.frame")
expect_equal(nrow(bistablehistory::historyef(fit, summary = FALSE)), 2 * samplesN)
# tau
expect_s3_class(bistablehistory::history_tau(fit), "data.frame")
expect_equal(nrow(bistablehistory::history_tau(fit, summary = FALSE)), samplesN)
expect_equal(ncol(bistablehistory::history_tau(fit, summary = FALSE)), 1)
# mixed state
expect_s3_class(bistablehistory::history_mixed_state(fit), "data.frame")
# mean history
expect_equal(nrow(extract_history(fit)), fit$data$rowsN)
expect_equal(ncol(extract_history(fit)), 2)
# predictions
expect_equal(length(predict(fit)), fit$data$rowsN)
expect_equal(length(predict(fit, full_length = FALSE)), fit$data$clearN)
expect_equal(nrow(predict(fit, summary = FALSE)), samplesN)
expect_equal(ncol(predict(fit, summary = FALSE)), fit$data$rowsN)
expect_equal(ncol(predict(fit, summary = FALSE, full_length = FALSE)), fit$data$clearN)
expect_equal(nrow(predict(fit, summary = FALSE)), samplesN)
# not fixed effect, should be null
expect_message(fixef(fit))
expect_equal(fixef(fit), NULL)
# fixed effects
fit <- readRDS("fit-fixed.RDS")
sampler_params <- rstan::get_sampler_params(fit$stanfit, inc_warmup = FALSE)
samplesN <- dim(sampler_params[[1]])[1] * length(sampler_params)
expect_s3_class(fixef(fit), "data.frame")
expect_equal(nrow(fixef(fit)), 2)
expect_equal(nrow(fixef(fit, summary=FALSE)), 2 * samplesN)
expect_equal(ncol(fixef(fit, summary=FALSE)), 3)
})
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