Nothing
test_that("warnings for spreads", {
dat <- fuzzydat$nas
expect_warning(fuzzylm(y~x,dat, method="fls", fuzzy.left.y = "yl", fuzzy.right.y = "yl"),
"spreads detected")
expect_warning(fuzzylm(y~x,dat, method="fls", fuzzy.left.y = "yl", fuzzy.right.y = "yl", silent = TRUE),
regexp = NA)
})
test_that("error for incorrect number of spreads for nsTFN", {
expect_error(fuzzylm(y ~ x, data = fuzzydat$dia, method = "fls", fuzzy.left.y = "yl"),
regexp = "Only one dependent variable with two spreads allowed for the FLS method")
})
test_that("warning on outlier in OPLR method", {
expect_warning(fuzzylm(y ~ x, fuzzydat$hun, "oplr", , , "yl", "yl"),
"one outlier")
})
test_that("error on multiple outliers in OPLR method", {
dat = fuzzydat$hun
dat[1,3] = 4.0
expect_error(fuzzylm(y ~ x, dat, "oplr", , , "yl", "yl"),
regexp = "Multiple outliers detected")
})
test_that("error on partial matching in fuzzify", {
expect_error(fuzzify(1:5, method = "m"),
"not uniquely matched")
})
test_that("error on length of grouping elements in fuzzify", {
expect_error(fuzzify(1:3, c("n", "m")),
"same length")
})
test_that("error on incorrect length of the err argument in fuzzify", {
expect_error(fuzzify(1:3, , "err", err = 1:2),
"spreads included in the err argument")
})
test_that("number of rows for the error method with non-symmetric spreads", {
expect_equal(nrow(fuzzify(1:2, , "err", err = 1:4)),
2,
tolerance = 1e-6)
})
test_that("parse variable names in fuzzify", {
dat = data.frame(ex = 1:3, res = c(1,1,2))
f = fuzzify(dat$ex, dat$res, dimnames = list("ex", "res"))
expect_equal(colnames(f),
c("exc", "exl", "exr", "res"))
expect_equal(colnames(fuzzify(dat$ex, dat$res)),
c("Ac", "Al", "Ar", "y"))
expect_equal(colnames(fuzzify(dat)),
c("exc", "resc", "exl", "resl", "exr", "resr", "y"))
})
test_that("warning on wordy dimnames in fuzzify", {
expect_error(fuzzify(1:3, method = "med", dimnames = list(c("a", "b"), "c")),
"does not correspond to dimensions")
expect_error(fuzzify(matrix(1:6, ncol = 2), method = "mea", dimnames = list("a", "c")),
"does not correspond to dimensions")
})
test_that("error on regression without intercept", {
expect_error(fuzzylm(y ~ x - 1, data = fuzzydat$lee, method = "plrls"),
"intercept")
})
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