```
test_that("kernelboot function", {
fun1 <- function(data) coef(lm(mpg ~ ., data = data))
fun2 <- function(data) mean(data)
fun3 <- function(data) data
fun_err <- function(data) stop()
dat <- mtcars
datMtx <- as.matrix(dat)
expect_message(expect_error(kernelboot(dat, fun_err, R = 10)))
expect_silent(kernelboot(dat, fun1, R = 10))
expect_silent(kernelboot(dat$mpg, fun2, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, fun3, R = 10, kernel = "gaussian"))
# this test behaves strangely on Windows
# expect_silent(kernelboot(dat, fun1, R = 10, parallel = TRUE))
# standard bootstrap
expect_equal(kernelboot(dat, fun1, R = 10, kernel = "gaussian", ignore = colnames(dat))$param$kernel, "none")
expect_equal(kernelboot(dat, fun1, R = 10, bw = 0)$param$kernel, "none")
expect_equal(kernelboot(dat$mpg, fun2, R = 10, bw = 0)$param$kernel, "none")
expect_equal(kernelboot(dat, fun1, R = 10, kernel = "none")$param$kernel, "none")
expect_equal(kernelboot(dat$mpg, fun2, R = 10, kernel = "none")$param$kernel, "none")
expect_equal(kernelboot(dat, fun1, R = 10, kernel = "none")$type, "multivariate")
expect_equal(kernelboot(dat$mpg, fun2, R = 10, kernel = "none")$type, "univariate")
kernels <- c("multivariate", "gaussian", "epanechnikov", "rectangular",
"triangular", "biweight", "cosine", "optcosine", "none")
for (k in kernels) {
expect_silent(kernelboot(dat, identity, R = 10, kernel = substr(k, 1, 1), bw = 1))
expect_silent(kernelboot(matrix(0, 0L, 0L), identity, R = 10, kernel = k, bw = 1))
expect_silent(kernelboot(matrix(0, 0L, 1L), identity, R = 10, kernel = k, bw = 1))
expect_silent(kernelboot(matrix(0, 1L, 0L), identity, R = 10, kernel = k, bw = 1))
expect_equal(kernelboot(dat, fun1, R = 10, kernel = k)$param$kernel, k)
expect_equal(kernelboot(datMtx, colMeans, R = 10, kernel = k)$param$kernel, k)
# handling single-column matrix
expect_equal(kernelboot(dat[, 1, drop = FALSE], colMeans, R = 10, kernel = k)$param$kernel, k)
expect_equal(kernelboot(datMtx[, 1, drop = FALSE], colMeans, R = 10, kernel = k)$param$kernel, k)
}
expect_equal(kernelboot(dat, fun1, R = 10, kernel = "multivariate")$type, "multivariate")
# ignore multivariate and simple bootstrap
for (k in kernels[-c(1L, length(kernels))]) {
expect_warning(kernelboot(numeric(0), identity, R = 10, kernel = k, bw = 1))
expect_equal(kernelboot(dat, fun1, R = 10, kernel = k)$type, "product")
expect_equal(kernelboot(dat$mpg, fun2, R = 10, kernel = k)$param$kernel, k)
expect_equal(kernelboot(dat$mpg, fun2, R = 10, kernel = k)$type, "univariate")
}
expect_message(expect_equal(kernelboot(dat$mpg, fun2, R = 10)$param$kernel, "gaussian"))
expect_message(expect_equal(kernelboot(dat$mpg, fun2, R = 10, kernel = "multivariate")$param$kernel, "gaussian"))
expect_equal(kernelboot(dat$mpg, fun2, R = 10, kernel = "multivariate")$type, "univariate")
expect_error(kernelboot(as.list(1:10), fun2, R = 10))
dat[5, 1] <- NA
expect_error(kernelboot(dat, fun1, R = 10))
expect_error(kernelboot(dat$mpg, fun2, R = 10))
expect_error(kernelboot(dat$mpg, fun3, R = 10))
dat <- mtcars
dat[5, 1] <- Inf
expect_error(kernelboot(dat, fun1, R = 10))
expect_error(kernelboot(dat$mpg, fun2, R = 10))
expect_error(kernelboot(dat$mpg, fun3, R = 10))
dat <- mtcars
dat[] <- 0
expect_silent(kernelboot(dat, fun1, R = 10))
expect_silent(kernelboot(dat$mpg, fun2, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, fun3, R = 10, kernel = "gaussian"))
dat <- mtcars
n <- nrow(dat)
k <- ncol(dat)
w <- rep(1, n)
expect_silent(kernelboot(dat, fun1, weights = w, R = 10))
expect_silent(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
w <- 1
expect_silent(kernelboot(dat, fun1, weights = w, R = 10))
expect_silent(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
w <- rep(NA, n)
expect_error(kernelboot(dat, fun1, weights = w, R = 10))
expect_error(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
w <- rep(-Inf, n)
expect_error(kernelboot(dat, fun1, weights = w, R = 10))
expect_error(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
w <- rep(Inf, n)
expect_error(kernelboot(dat, fun1, weights = w, R = 10))
expect_error(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
w <- rep(1/n, n-1)
expect_error(kernelboot(dat, fun1, weights = w, R = 10))
expect_error(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
w <- rep(1/n, n+1)
expect_error(kernelboot(dat, fun1, weights = w, R = 10))
expect_error(kernelboot(dat$mpg, weights = w, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, weights = w, fun3, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat, fun1, bw = diag(k), R = 10))
expect_silent(kernelboot(dat, fun1, bw = rep(1, k), R = 10))
expect_silent(kernelboot(dat$mpg, bw = 1, fun2, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, bw = 1, fun3, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat, fun1, bw = rep(-1, k), R = 10))
expect_error(kernelboot(dat$mpg, bw = -1, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = -1, fun3, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat, fun1, bw = matrix(NA, k, k), R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(NA, k), R = 10))
expect_error(kernelboot(dat$mpg, bw = NA, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = NA, fun3, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat, fun1, bw = matrix(Inf, k, k), R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(Inf, k), R = 10))
expect_error(kernelboot(dat$mpg, bw = Inf, fun2, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = Inf, fun3, R = 10, kernel = "gaussian"))
a <- 1
expect_silent(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_silent(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_silent(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
a <- -1
expect_error(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_error(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
a <- NA
expect_error(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_error(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
a <- Inf
expect_error(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_error(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
a <- 1:10
expect_silent(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_silent(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_silent(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
a <- matrix(1, 10, 10)
expect_error(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_error(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
a <- as.data.frame(matrix(1, 10, 10))
expect_error(kernelboot(dat, fun1, bw = diag(k), adjust = a, R = 10))
expect_error(kernelboot(dat, fun1, bw = rep(1, k), adjust = a, R = 10))
expect_error(kernelboot(dat$mpg, bw = 1, fun2, adjust = a, R = 10, kernel = "gaussian"))
expect_error(kernelboot(dat$mpg, bw = 1, fun3, adjust = a, R = 10, kernel = "gaussian"))
dat <- mtcars
expect_silent(kernelboot(dat, fun1, R = 10, kernel = "cosine"))
expect_silent(kernelboot(dat$mpg, fun2, R = 10, kernel = "cosine"))
expect_silent(kernelboot(dat$mpg, fun3, R = 10, kernel = "cosine"))
dat <- mtcars
# expect_message(kernelboot(dat, fun1, R = 10, ignore = colnames(dat)))
expect_silent(kernelboot(dat$mpg, fun2, R = 10, ignore = colnames(dat), kernel = "gaussian"))
expect_silent(kernelboot(dat$mpg, fun3, R = 10, ignore = colnames(dat), kernel = "gaussian"))
})
```

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