From b5ee48a86e4b1d4c05aaadb80b44954e2e994ebc Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 27 May 2020 07:12:51 +0200 Subject: Add docs generated using released version 0.9.52 --- docs/reference/confint.mkinfit.html | 78 ++++++++++++++++--------------------- 1 file changed, 34 insertions(+), 44 deletions(-) (limited to 'docs/reference/confint.mkinfit.html') diff --git a/docs/reference/confint.mkinfit.html b/docs/reference/confint.mkinfit.html index 0686c7bb..a9080c39 100644 --- a/docs/reference/confint.mkinfit.html +++ b/docs/reference/confint.mkinfit.html @@ -79,7 +79,7 @@ method of Venzon and Moolgavkar (1988)." /> mkin - 0.9.50.3 + 0.9.50.2 @@ -116,9 +116,6 @@ method of Venzon and Moolgavkar (1988)." />
  • Example evaluation of NAFTA SOP Attachment examples
    • -
  • - Some benchmark timings -
  • @@ -171,8 +168,7 @@ method of Venzon and Moolgavkar (1988).

    method = c("quadratic", "profile"), transformed = TRUE, backtransform = TRUE, - cores = parallel::detectCores(), - rel_tol = 0.01, + cores = round(detectCores()/2), quiet = FALSE, ... ) @@ -226,12 +222,6 @@ 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 @@ -281,28 +271,28 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, 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 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 +#> 3.430 0.000 3.432
    # 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 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% + 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: length of 'dimnames' [2] not equal to array extent
    #> Timing stopped at: 0.012 0.042 0.211
    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 #> f_parent_to_m1 0.471328495 5.611550e-01 #> sigma 2.535612399 3.985263e+00
    ci_quadratic_transformed <- confint(f_d_1, method = "quadratic") ci_quadratic_transformed
    #> 2.5% 97.5% -#> parent_0 96.403839460 1.027931e+02 +#> parent_0 96.403839476 1.027931e+02 #> k_parent 0.090823790 1.072543e-01 #> k_m1 0.004012216 6.897547e-03 #> f_parent_to_m1 0.469118713 5.595960e-01 #> sigma 2.396089689 3.854918e+00
    ci_quadratic_untransformed <- confint(f_d_1, method = "quadratic", transformed = FALSE) ci_quadratic_untransformed
    #> 2.5% 97.5% -#> parent_0 96.403839413 1.027931e+02 +#> parent_0 96.403839429 1.027931e+02 #> k_parent 0.090491931 1.069035e-01 #> k_m1 0.003835483 6.685819e-03 -#> f_parent_to_m1 0.469113365 5.598386e-01 +#> f_parent_to_m1 0.469113364 5.598386e-01 #> sigma 2.396089689 3.854918e+00
    # Against the expectation based on Bates and Watts (1988), the confidence # intervals based on the internal parameter transformation are less # congruent with the likelihood based intervals. Note the superiority of the @@ -314,7 +304,7 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, #> k_parent TRUE TRUE #> k_m1 FALSE FALSE #> f_parent_to_m1 TRUE FALSE -#> sigma FALSE FALSE
    signif(rel_diffs_transformed, 3)
    #> 2.5% 97.5% +#> sigma FALSE TRUE
    signif(rel_diffs_transformed, 3)
    #> 2.5% 97.5% #> parent_0 0.000541 0.000222 #> k_parent 0.000960 0.000900 #> k_m1 0.030700 0.029100 @@ -335,16 +325,16 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, #> f_parent_to_m1 0.471328495 5.611550e-01 #> sigma 2.535612399 3.985263e+00
    ci_quadratic_transformed_ff <- confint(f_d_2, method = "quadratic") ci_quadratic_transformed_ff
    #> 2.5% 97.5% -#> parent_0 96.403839460 1.027931e+02 +#> parent_0 96.403839476 1.027931e+02 #> k_parent 0.090823790 1.072543e-01 #> k_m1 0.004012216 6.897547e-03 #> f_parent_to_m1 0.469118713 5.595960e-01 #> sigma 2.396089689 3.854918e+00
    ci_quadratic_untransformed_ff <- confint(f_d_2, method = "quadratic", transformed = FALSE) ci_quadratic_untransformed_ff
    #> 2.5% 97.5% -#> parent_0 96.403839413 1.027931e+02 +#> parent_0 96.403839429 1.027931e+02 #> k_parent 0.090491931 1.069035e-01 #> k_m1 0.003835483 6.685819e-03 -#> f_parent_to_m1 0.469113365 5.598386e-01 +#> f_parent_to_m1 0.469113364 5.598386e-01 #> sigma 2.396089689 3.854918e+00
    rel_diffs_transformed_ff <- abs((ci_quadratic_transformed_ff - ci_profile_ff)/ci_profile_ff) rel_diffs_untransformed_ff <- abs((ci_quadratic_untransformed_ff - ci_profile_ff)/ci_profile_ff) # While the confidence interval for the parent rate constant is closer to @@ -356,17 +346,17 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, #> k_parent TRUE TRUE #> k_m1 FALSE FALSE #> f_parent_to_m1 TRUE FALSE -#> sigma FALSE FALSE
    rel_diffs_transformed_ff
    #> 2.5% 97.5% -#> parent_0 0.0005408080 0.0002217794 +#> sigma FALSE TRUE
    rel_diffs_transformed_ff
    #> 2.5% 97.5% +#> parent_0 0.0005408078 0.0002217796 #> k_parent 0.0009596417 0.0009003876 -#> k_m1 0.0307277370 0.0290579182 -#> f_parent_to_m1 0.0046884130 0.0027782556 -#> sigma 0.0550252516 0.0327066836
    rel_diffs_untransformed_ff
    #> 2.5% 97.5% -#> parent_0 0.0005408085 0.0002217799 -#> k_parent 0.0046100096 0.0023730229 -#> k_m1 0.0146746469 0.0025301011 -#> f_parent_to_m1 0.0046997599 0.0023460223 -#> sigma 0.0550252516 0.0327066836
    +#> k_m1 0.0307277372 0.0290579184 +#> f_parent_to_m1 0.0046884131 0.0027782558 +#> sigma 0.0550252516 0.0327066836
    rel_diffs_untransformed_ff
    #> 2.5% 97.5% +#> parent_0 0.0005408083 0.000221780 +#> k_parent 0.0046100096 0.002373023 +#> k_m1 0.0146746467 0.002530101 +#> f_parent_to_m1 0.0046997600 0.002346022 +#> sigma 0.0550252516 0.032706684
    # The profiling for the following fit does not finish in a reasonable time, # therefore we use the quadratic approximation m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")), @@ -375,19 +365,19 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, use_of_ff = "max", quiet = TRUE) DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data f_tc_2 <- mkinfit(m_synth_DFOP_par, DFOP_par_c, error_model = "tc", - error_model_algorithm = "direct", quiet = TRUE) -confint(f_tc_2, method = "quadratic")
    #> 2.5% 97.5% -#> parent_0 94.59613833 106.19939215 -#> k_M1 0.03760542 0.04490759 -#> k_M2 0.00856874 0.01087675 -#> f_parent_to_M1 0.02146166 0.62023888 -#> f_parent_to_M2 0.01516502 0.37975343 -#> k1 0.27389751 0.33388078 -#> k2 0.01861456 0.02250379 -#> g 0.67194349 0.73583256 -#> sigma_low 0.25128383 0.83992146 -#> rsd_high 0.04041100 0.07662001
    confint(f_tc_2, "parent_0", method = "quadratic")
    #> 2.5% 97.5% -#> parent_0 94.59614 106.1994
    # } + error_model_algorithm = "direct", quiet = TRUE)
    #> Warning: Optimisation did not converge: +#> iteration limit reached without convergence (10)
    confint(f_tc_2, method = "quadratic")
    #> 2.5% 97.5% +#> parent_0 95.654015524 105.79279749 +#> k_M1 0.037723773 0.04447598 +#> k_M2 0.008586438 0.01078076 +#> f_parent_to_M1 0.230403596 0.61953014 +#> f_parent_to_M2 0.162909765 0.38019017 +#> k1 0.275434628 0.33331386 +#> k2 0.018602188 0.02249211 +#> g 0.675149759 0.73520889 +#> sigma_low 0.251416929 0.84272023 +#> rsd_high 0.040371818 0.07666540
    confint(f_tc_2, "parent_0", method = "quadratic")
    #> 2.5% 97.5% +#> parent_0 95.65402 105.7928
    # }