Nothing
test_that("SVC_mle call creates correct objects", {
## ---- toy example ----
## We use the sampled, i.e., onde dimensional SVCs
data(SVCdata)
# sub-sample data to have feasible run time for example
set.seed(123)
id <- sample(length(SVCdata$locs), 50)
## SVC_mle call with matrix arguments
# Test on the side: Internally, the spam.trivalues option is set to TRUE.
# We check that it is set back to the original value after the call.
options(spam.trivalues = FALSE)
expect_identical(FALSE, getOption("spam.trivalues"))
fit1 <- with(SVCdata, SVC_mle(
y[id], X[id, ], locs[id],
control = SVC_mle_control(profileLik = TRUE, cov.name = "mat32")))
expect_identical(FALSE, getOption("spam.trivalues"))
## SVC_mle call with formula
df <- with(SVCdata, data.frame(y = y[id], X = X[id, -1]))
fit2 <- SVC_mle(
y ~ X, data = df, locs = SVCdata$locs[id],
control = SVC_mle_control(profileLik = TRUE, cov.name = "mat32")
)
## SVC_mle call with formula
df <- with(SVCdata, data.frame(y = y[id], X = X[id, -1]))
fit2_2 <- SVC_mle(
y ~ X, data = df, RE_formula = ~ 1, locs = SVCdata$locs[id],
control = SVC_mle_control(profileLik = TRUE, cov.name = "mat32")
)
expect_null(fit1$formula, fit1$RE_formula)
expect_identical(fit2$formula, y ~ X)
expect_identical(fit2$RE_formula, y ~ X)
expect_identical(fit2_2$formula, y ~ X)
expect_identical(fit2_2$RE_formula, ~ 1)
})
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