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benchmark vs lme4 #8

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@bdilday

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@bdilday

For a binomial outcome we can compare execution time tolme4::glmer. These are the current results on an example problem.

microbenchmark::microbenchmark(mnre_mod = mnre_fit(y ~ 1 + (1|fct01) + (1|fct02), data=ev$fr, verbose=0), glmer_mod <- glmer(ev$frm, data=ev$fr, family='binomial', nAGQ=0), times = 5)Unit: milliseconds                                                                         expr       min        lq                                                                     mnre_mod 9442.0576 9480.7341 glmer_mod <- glmer(ev$frm, data = ev$fr, family = "binomial",      nAGQ = 0)  893.5765  904.6866      mean    median        uq      max neval 9532.4786 9505.4875 9606.3683 9627.746     5  981.5733  921.1398  959.1317 1229.332     5

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