Nothing
context("covTS")
## require (numDeriv) now in 'Depends'
precision <- 1e-6
d <- 3; n <- 10
set.seed(1234)
## utility function
covAsVec <- function(par, object, index, ...) {
coef(object) <- par
C <- covMat(object = object, X = X, compGrad = TRUE, index = index)
grad <- attr(C, "gradient")
C <- C[row(C) <= col(C)]
grad <- grad[row(grad) <= col(grad)]
attr(C, "gradient") <- grad
C
}
## define a covTS
myCov <- covTS(d = d, kernel = "k1PowExp",
dep = c(range = "input", shape = "input"),
value = c(range = 0.1, shape = 0.6))
## choose a design and parameter values
X <- array(runif(n * d), dim = c(n, d),
dimnames = list(NULL, inputNames(myCov)))
Theta <- simulPar(object = myCov, n = 10L)
index <- 1
theta <- Theta[1, ]
res <- covAsVec(theta, myCov, index = index)
grad.check <- jacobian(covAsVec, theta, object = myCov, index = index)
mat <- cbind(check = grad.check[ , index], prog = attr(res, "gradient"))
err <- max(abs(apply(mat, 1, function (x) mean(abs(diff(x))))))
test_that(desc = "gradient of a \"covTS\" structure",
code = expect_true(err < precision))
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