# From SamplerCompare, (c) 2010 Madeleine Thompson # This script contains a couple miscellaneous tests. library(SamplerCompare) # Make sure the R-C glue for distributions works by creating C and # R versions of the same 2-D Gaussian and making sure their log density # and its gradient agree on a randomly chosen point. N2.C <- make.c.dist(2, 'Gauss2-C', 'Gauss2_log_dens', c(1, 2, 0.8), mean=c(1,2)) N2.R <- make.gaussian(c(1,2), rho=0.8) x <- runif(2) stopifnot(abs(N2.C$log.density(x)-N2.R$log.density(x)) < 1e-08) stopifnot(max(abs(N2.C$grad.log.density(x)-N2.R$grad.log.density(x))) < 1e-08) # Make sure multivariate Gamma distributions have a log density # that matches both dgamma and their gradient. k <- c(1,2) theta <- c(3,4) ds <- make.mv.gamma.dist(k, theta) x <- runif(2) stopifnot(abs(sum(dgamma(x, k, scale=theta, log=TRUE)) - ds$log.density(x)) < 1e-5) check.dist.gradient(ds, x)
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