All samplers run for 1024 iterations.
X <- bench::mark(
"Metropolis-Hastings" = {samplr::sampler_mh(1, "norm", c(0,1), sigma_prop=1)},
"MC3" = {samplr::sampler_mc3(1, "norm", c(0,1), sigma_prop=1)},
"Hamiltonian Monte-Carlo" = {samplr::sampler_hmc(1, "norm", c(0,1))},
"REC" = {samplr::sampler_rec(1, "norm", c(0,1))},
"MCHMC" = {samplr::sampler_mchmc(1, "norm", c(0,1), )},
"MCREC" = {samplr::sampler_mcrec(1, "norm", c(0,1))},
check = FALSE, iterations = 50
)
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
knitr::kable(as.data.frame(X[,c("expression", "min", "median")]))
expression | min | median |
---|---|---|
Metropolis-Hastings | 1.52ms | 1.57ms |
MC3 | 14.43ms | 14.91ms |
Hamiltonian Monte-Carlo | 11.66ms | 11.88ms |
REC | 11.81ms | 12.06ms |
MCHMC | 80.4ms | 84.46ms |
MCREC | 80.69ms | 86.36ms |