Nothing
library(quantdr)
test_that("the function returns an error when y is multivariate response", {
set.seed(1234)
n <- 100
p <- 2
x <- matrix(rnorm(n * p), n, p)
error <- rnorm(n); y <- x^2 + error
tau <- 0.5
expect_error(llqr(x, y, tau = tau), )
})
test_that("the function returns an error when the number of observations
for y and x differ", {
set.seed(1234)
n <- 100
p <- 2
x <- matrix(rnorm(n * p), n, p)
error <- rnorm(n); y <- x[, 1]^2 + error
tau <- 0.5
expect_error(llqr(x, y[1:(n / 2)], tau = tau), )
})
test_that("the quantile level needs to be strictly between 0 and 1", {
set.seed(1234)
n <- 100
x <- rnorm(n)
error <- rnorm(n)
y <- (x + 1)^3 + 0.1 * (x - 2)^3 + error
tau <- -0.1
expect_error(llqr(x, y, tau = tau), )
})
test_that("the function returns an error for NA", {
set.seed(1234)
n <- 100
x <- rnorm(n)
error <- rnorm(n)
y <- (x + 1)^3 + 0.1 * (x - 2)^3 + error
y[1] <- 0 / 0
tau <- 0.5
expect_error(llqr(x, y, tau = tau), )
})
test_that("quantile level needs to be one number", {
set.seed(1234)
n <- 100
x <- rnorm(n)
error <- rnorm(n)
y <- (x + 1)^3 + 0.1 * (x - 2)^3 + error
tau <- c(0.2, 0.5)
expect_error(llqr(x, y, tau = tau), )
})
test_that("n should be greater than p", {
set.seed(1234)
n <- 20
p <- 40
x <- matrix(rnorm(n * p), n, p)
error <- rnorm(n); y <- x[, 1]^2 + error
tau <- 0.5
expect_error(llqr(x, y, tau = tau), )
})
test_that("the function gives an error message when the dimension of
x0 is less than that of x", {
set.seed(1234)
n <- 100
p <- 2
x <- matrix(rnorm(n * p), n, p)
error <- rnorm(n); y <- x[, 1]^2 + error
tau <- 0.5
x0 <- 1
expect_error(llqr(x, y, tau = tau, x0 = x0)$ll_est, )
})
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