Nothing
test_that("predict works", {
rmvn <- function(n, mu = 0, V = matrix(1)){
p <- length(mu)
if(any(is.na(match(dim(V),p))))
stop("Dimension not right!")
D <- chol(V)
t(matrix(rnorm(n*p), ncol=p)%*%D + rep(mu,rep(n,p)))
}
set.seed(5)
n <- 200
coords <- cbind(runif(n,0,1), runif(n,0,1))
set.seed(2)
x <- as.matrix(runif(n),n,1)
sigma.sq = 10
phi = 1
tau.sq = 0.1
D <- as.matrix(dist(coords))
R <- exp(-phi*D)
w <- rmvn(1, rep(0,n), sigma.sq*R)
y <- rnorm(n, 10*sin(pi * x) + w, sqrt(tau.sq))
set.seed(1)
est_known <- RFGLS_estimate_spatial(coords, y, x, ntree = 10, cov.model = "exponential",
nthsize = 20, sigma.sq = sigma.sq, tau.sq = tau.sq,
phi = phi)
Xtest <- matrix(seq(0,1, by = 1/10000), 10001, 1)
RFGLS_predict_known <- RFGLS_predict(est_known, Xtest)
expect_true(is.matrix(RFGLS_predict_known$predicted_matrix))
expect_equal(dim(RFGLS_predict_known$predicted_matrix), c(10001,10))
expect_length(RFGLS_predict_known$predicted, 10001)
})
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