Nothing
## Simple example with few coefficients
R <- matrix(c(1, 2, 0,
3, 1, 2,
2, 1, 1,
1, 2, 3,
2, 1, 1,
1, 0, 2), nrow = 6, byrow = TRUE)
colnames(R) <- c("apple", "banana", "orange")
tol <- 1e-6
model_fruits1 <- PlackettLuce(rankings = R)
model_fruits2 <- PlackettLuce(rankings = R[-5,],
weights = c(1, 1, 2, 1, 1))
test_that("output of print.PlackettLuce is correct", {
expect_snapshot_output(print(model_fruits1))
})
test_that("output of print.coef.PlackettLuce is correct", {
expect_snapshot_output(print(coef(model_fruits1)))
})
test_that("output of print.summary.PlackettLuce is correct", {
expect_snapshot_output(print(summary(model_fruits1)))
})
test_that("output of fitted.PlackettLuce is correct", {
expect_snapshot_value(fitted(model_fruits1),
tolerance = tol, style = "json2")
expect_snapshot_value(fitted(model_fruits1, aggregate = FALSE),
tolerance = tol, style = "json2")
expect_snapshot_value(fitted(model_fruits1, free = FALSE),
tolerance = tol, style = "json2")
})
test_that("output of fitted.PlackettLuce is correct [weights]", {
# fitted the same apart from ranking ID(s) when aggregate
expect_equal(fitted(model_fruits1, aggregate = TRUE)[-3],
fitted(model_fruits2, aggregate = TRUE)[-3])
# non-aggregated for weighted same as aggregate for unweighted
expect_equal(fitted(model_fruits1, aggregate = TRUE)[-3],
fitted(model_fruits2, aggregate = FALSE)[-3],
ignore_attr = TRUE)
})
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