From 675a733fa2acc08daabb9b8b571c7d658f281f73 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 26 May 2020 18:38:51 +0200 Subject: Use all cores per default, confint tolerance Also, use more intelligent starting values for the variance of the random effects for saemix. While this does not appear to speed up the convergence, it shows where this variance is greatly reduced by using mixed-effects models as opposed to the separate independent fits. --- docs/reference/confint.mkinfit.html | 20 +++++++++++++++----- 1 file changed, 15 insertions(+), 5 deletions(-) (limited to 'docs/reference/confint.mkinfit.html') diff --git a/docs/reference/confint.mkinfit.html b/docs/reference/confint.mkinfit.html index 190494bc..0686c7bb 100644 --- a/docs/reference/confint.mkinfit.html +++ b/docs/reference/confint.mkinfit.html @@ -79,7 +79,7 @@ method of Venzon and Moolgavkar (1988)." /> mkin - 0.9.50.2 + 0.9.50.3 @@ -116,6 +116,9 @@ method of Venzon and Moolgavkar (1988)." />
  • Example evaluation of NAFTA SOP Attachment examples
    • +
  • + Some benchmark timings +
  • @@ -168,7 +171,8 @@ method of Venzon and Moolgavkar (1988).

    method = c("quadratic", "profile"), transformed = TRUE, backtransform = TRUE, - cores = round(detectCores()/2), + cores = parallel::detectCores(), + rel_tol = 0.01, quiet = FALSE, ... ) @@ -222,6 +226,12 @@ their confidence intervals?

    cores

    The number of cores to be used for multicore processing. On Windows machines, cores > 1 is currently not supported.

    + + + rel_tol +

    If the method is 'profile', what should be the accuracy +of the lower and upper bounds, relative to the estimate obtained from +the quadratic method?

    quiet @@ -270,13 +280,13 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) f_d_1 <- mkinfit(SFO_SFO, subset(FOCUS_2006_D, value != 0), quiet = TRUE) -system.time(ci_profile <- confint(f_d_1, method = "profile", cores = 1, quiet = TRUE))
    #> User System verstrichen -#> 3.410 0.000 3.412
    # Using more cores does not save much time here, as parent_0 takes up most of the time +system.time(ci_profile <- confint(f_d_1, method = "profile", cores = 1, quiet = TRUE))
    #> user system elapsed +#> 3.689 0.991 3.361
    # Using more cores does not save much time here, as parent_0 takes up most of the time # If we additionally exclude parent_0 (the confidence of which is often of # minor interest), we get a nice performance improvement from about 50 # seconds to about 12 seconds if we use at least four cores system.time(ci_profile_no_parent_0 <- confint(f_d_1, method = "profile", - c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = n_cores))
    #> Profiling the likelihood
    #> Warning: scheduled cores 1, 2, 3 encountered errors in user code, all values of the jobs will be affected
    #> Error in dimnames(x) <- dn: Länge von 'dimnames' [2] ungleich der Arrayausdehnung
    #> Timing stopped at: 0.008 0.044 0.201
    ci_profile
    #> 2.5% 97.5% + c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = n_cores))
    #> Profiling the likelihood
    #> Warning: scheduled cores 2, 1, 3 encountered errors in user code, all values of the jobs will be affected
    #> Error in dimnames(x) <- dn: length of 'dimnames' [2] not equal to array extent
    #> Timing stopped at: 0.007 0.042 0.193
    ci_profile
    #> 2.5% 97.5% #> parent_0 96.456003640 1.027703e+02 #> k_parent 0.090911032 1.071578e-01 #> k_m1 0.003892605 6.702778e-03 -- cgit v1.2.1