Nothing
make.mvn.prior <- texmex:::.make.mvn.prior
make.quad.prior <- texmex:::.make.quadratic.penalty
make.spd.matrix <- texmex:::.random.spd.matrix
for (count in 1:100) {
dimn <- sample(10, size=1)
cov.matrix <- make.spd.matrix(dimn)
centre <- rexp(dimn)
mvnprior <- make.mvn.prior(list(centre, cov.matrix))
point <- rexp(dimn)
expect_equal(mvnprior(point),
dmvnorm(point, centre, cov.matrix, log=TRUE),
label="efficient.closures: multivariate Gaussian prior")
quadprior <- make.quad.prior(list(centre, cov.matrix))
expect_equal(quadprior(point),
mahalanobis(point, centre, cov.matrix),
label="efficient.closures: Mahalanobis distance")
# or "A-norm", as it's otherwise called
}
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