Nothing
library(Countr)
library(rbenchmark)
source("mcShaneCode.R")
data(fertility)
## config: choose parameters (selection process not shown here)
children <- fertility$children
shape <- 1.116
scale <- rep(2.635, length(children))
rep <- 1000
nstepsConv <- c(132, 24, 132, 24, 132, 36)
ntermsSeries <- c(20, 17)
conv_series_acc <- 1e-7
## performance model
perf <- benchmark(direct0 =
dWeibullCount_loglik(children, shape, scale, "conv_direct",
1, TRUE, nstepsConv[1],
conv_extrap = FALSE),
direct1 =
dWeibullCount_loglik(children, shape, scale, "conv_direct",
1, TRUE, nstepsConv[2],
conv_extrap = TRUE),
naive0 =
dWeibullCount_loglik(children, shape, scale, "conv_naive",
1, TRUE, nstepsConv[3],
conv_extrap = FALSE),
naive1 = dWeibullCount_loglik(children, shape, scale,
"conv_naive",
1, TRUE, nstepsConv[4],
conv_extrap = TRUE),
dePril0 = dWeibullCount_loglik(children, shape, scale,
"conv_dePril",
1, TRUE, nstepsConv[5],
conv_extrap = FALSE),
dePril1 = dWeibullCount_loglik(children, shape, scale,
"conv_dePril",
1, TRUE, nstepsConv[6],
conv_extrap = TRUE),
series_mat =
dWeibullCount_loglik(children, shape, scale,
"series_mat", 1, TRUE,
series_terms = ntermsSeries[1]),
series_acc =
dWeibullCount_loglik(children, shape, scale,
"series_acc", 1, TRUE,
series_terms = ntermsSeries[2],
series_acc_eps = conv_series_acc),
mcShane = dWeibullCount_McShane(scale, shape,
children, jmax = 150),
replications = rep, order = "relative",
columns = c("test", "replications", "relative", "elapsed")
)
print(perf)
save.image()
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