Nothing
test_that("structure and dimensions of sample_SVCdata are correct", {
n <- 10L
set.seed(123)
# SVC parameters
df.pars <- data.frame(
var = c(2, 0, 1),
scale = c(3, 1, 1),
mean = c(1, 2, 0)
)
# nugget standard deviation
tau <- 0.5
# sample locations
s <- sort(runif(n, min = 0, max = 10))
SVCdata <- sample_SVCdata(
df.pars = df.pars, nugget.sd = tau, locs = s, cov.name = "mat32"
)
expect_type(SVCdata, "list")
expect_identical(names(SVCdata), c("y", "X", "beta", "eps", "locs", "true_pars"))
expect_length(SVCdata$y, n)
expect_identical(dim(SVCdata$X), c(n, 3L))
expect_identical(dim(SVCdata$beta), c(n, 3L))
expect_length(SVCdata$eps, n)
expect_type(SVCdata$true_pars, "list")
expect_identical(dim(SVCdata$true_pars), c(4L, 3L))
expect_identical(SVCdata$true_pars[1:3, ], df.pars)
expect_identical(SVCdata$true_pars[4, 1], tau^2)
expect_identical(SVCdata$true_pars[4, 2], NA_real_)
expect_identical(SVCdata$true_pars[4, 3], NA_real_)
})
test_that("all possible four types of SVCs are possible", {
n <- 10L
set.seed(123)
# SVC parameters
df.pars <- data.frame(
var = c(2, 1, 0, 0),
scale = c(3, 1, 1, 1),
mean = c(10, 0, 2, 0)
)
# nugget standard deviation
tau <- 0.5
# sample locations
s <- sort(runif(n, min = 0, max = 10))
SVCdata <- sample_SVCdata(
df.pars = df.pars, nugget.sd = tau, locs = s, cov.name = "mat32"
)
# first SVC (FE + RE):
# mean greater 0
expect_true(all(SVCdata$beta[, 1] > 1))
# variation
expect_true(min(SVCdata$beta[, 1]) != max(SVCdata$beta[, 1]))
# second SVC (only RE):
# variation
expect_true(min(SVCdata$beta[, 2]) != max(SVCdata$beta[, 2]))
# third SVC (only FE):
# mean equal to 2
expect_true(all(SVCdata$beta[, 3] == 2))
# fourth SVC (neither FE nor RE):
# mean equal to 2
expect_true(all(SVCdata$beta[, 4] == 0))
})
test_that("providing an X matrix works", {
n <- 10L
set.seed(123)
# SVC parameters
df.pars <- data.frame(
var = c(2, 0, 1),
scale = c(3, 1, 1),
mean = c(1, 2, 0)
)
# nugget standard deviation
tau <- 0.5
# sample locations
s <- sort(runif(n, min = 0, max = 10))
# construct some covariate matrices
X2 <- matrix(1:(3*(n+1)), nrow = n+1, ncol = 3)
X3 <- matrix(1:(4*n), nrow = n, ncol = 4)
X4 <- as.data.frame(matrix(1:(3*n), nrow = n, ncol = 3))
expect_error(sample_SVCdata(
df.pars = df.pars, nugget.sd = tau, locs = s, cov.name = "mat32", X = X2
))
expect_error(sample_SVCdata(
df.pars = df.pars, nugget.sd = tau, locs = s, cov.name = "mat32", X = X3
))
expect_error(sample_SVCdata(
df.pars = df.pars, nugget.sd = tau, locs = s, cov.name = "mat32", X = X4
))
})
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