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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 | 842.4µs | 894.25µs |
| MC3 | 8.97ms | 9.69ms |
| Hamiltonian Monte-Carlo | 7.13ms | 8.26ms |
| REC | 7.14ms | 8.38ms |
| MCHMC | 52.92ms | 62.77ms |
| MCREC | 53.5ms | 59.32ms |
| tests | timeit |
|---|---|
| Metropolis-Hastings | 6.22ms |
| MC3 | 55.13ms |
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.