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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.