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Time Comparisons

Time Comparisons

All samplers run for 1024 iterations.

C++

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 1.14ms 1.25ms
MC3 12.23ms 13.38ms
Hamiltonian Monte-Carlo 9.71ms 10.95ms
REC 9.75ms 11.32ms
MCHMC 71.71ms 78.9ms
MCREC 70.08ms 80.26ms

MATLAB

tests timeit
Metropolis-Hastings 6.22ms
MC3 55.13ms

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