Nothing
context("GMRF matrices")
set.seed(1, kind="Mersenne-Twister", normal.kind="Inversion")
x <- seq(0, 1, 0.01)
dat <- data.frame(x, y=x*sin(5*x))
test_that("spline model works", {
sampler <- create_sampler(y ~ gen(factor = ~ spline(x, knots=15)),
linpred="fitted", data=dat)
sim <- MCMCsim(sampler, n.iter=500, verbose=FALSE)
summ <- summary(sim)
expect_true(max(abs(dat$y - summ$linpred_[, "Mean"])) < 0.02)
})
n <- 400L
dat <- data.frame(
x = runif(n),
f = as.factor(sample(1:10, n, replace = TRUE))
)
v <- rnorm(20, sd=0.5)
dat$y <- 1 + 2*dat$x + v[dat$f] + rnorm(n, sd=0.25)
test_that("custom precision matrix specification works", {
sampler <- create_sampler(
y ~ x + gen(factor = ~ custom(f, D=diag(10))),
data=dat
)
Q <- diag(10)
sampler <- create_sampler(
y ~ x + gen(factor = ~ custom(f, Q=Q)),
data=dat
)
Q2 <- Q
sampler <- create_sampler(
y ~ x + gen(factor = ~ custom(f, Q=Q2)),
data=dat
)
sim <- MCMCsim(sampler, verbose=FALSE)
summ <- summary(sim)
expect_true(0.1 < summ$sigma_[, "Mean"] && summ$sigma_[, "Mean"] < 0.4)
})
test_that("function compute_GMRF_matrices works", {
dat <- data.frame(f = 1:2)
expect_identical(dim(compute_GMRF_matrices(~ f, data=dat)$D), c(2L, 2L))
Q0 <- matrix(c(5,2,2,4), 2)
expect_identical(compute_GMRF_matrices(~ custom(f, Q=Q0), D=FALSE, data=dat)$Q, Q0)
})
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