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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 | 944.3µs | 1.32ms |
MC3 | 13.53ms | 15.96ms |
Hamiltonian Monte-Carlo | 9.98ms | 12.19ms |
REC | 10.42ms | 12.98ms |
MCHMC | 79.84ms | 86.51ms |
MCREC | 76.67ms | 87.77ms |
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.