From bc3825ae2d12c18ea3d3caf17eb23c93fef180b8 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 8 Oct 2020 09:31:35 +0200 Subject: Fix issues for release --- docs/dev/reference/confint.mkinfit.html | 86 ++++++++++++++++----------------- 1 file changed, 42 insertions(+), 44 deletions(-) (limited to 'docs/dev/reference/confint.mkinfit.html') diff --git a/docs/dev/reference/confint.mkinfit.html b/docs/dev/reference/confint.mkinfit.html index 074bed3e..5b683355 100644 --- a/docs/dev/reference/confint.mkinfit.html +++ b/docs/dev/reference/confint.mkinfit.html @@ -258,15 +258,15 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,

Examples

f <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
-confint(f, method = "quadratic")
#>                     2.5%      97.5%
-#> parent_0      71.8242430 93.1600766
-#> k_parent_sink  0.2109541  0.4440528
-#> sigma          1.9778868  7.3681380

+confint(f, method = "quadratic")
#>                2.5%      97.5%
+#> parent_0 71.8242430 93.1600766
+#> k_parent  0.2109541  0.4440528
+#> sigma     1.9778868  7.3681380

 # \dontrun{
-confint(f, method = "profile")
#> Profiling the likelihood
#>                     2.5%      97.5%
-#> parent_0      73.0641834 92.1392181
-#> k_parent_sink  0.2170293  0.4235348
-#> sigma          3.1307772  8.0628314

+confint(f, method = "profile")
#> Profiling the likelihood
#>                2.5%      97.5%
+#> parent_0 73.0641834 92.1392181
+#> k_parent  0.2170293  0.4235348
+#> sigma     3.1307772  8.0628314

 # Set the number of cores for the profiling method for further examples
 if (identical(Sys.getenv("NOT_CRAN"), "true")) {
   n_cores <- parallel::detectCores() - 1
@@ -279,30 +279,29 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,
 SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), quiet = TRUE)
 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 elapsed 
-#>   3.610   1.071   3.378 
# Using more cores does not save much time here, as parent_0 takes up most of the time
+f_d_1 <- mkinfit(SFO_SFO, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
#> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
system.time(ci_profile <- confint(f_d_1, method = "profile", cores = 1, quiet = TRUE))
#>    user  system elapsed 
+#>   3.810   0.964   3.430 
# 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: 0.005 0.04 0.206
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: 0.015 0.029 0.198
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       96.403839476 1.027931e+02
+#> parent_0       96.403839460 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       96.403839429 1.027931e+02
+#> parent_0       96.403839413 1.027931e+02
 #> k_parent        0.090491931 1.069035e-01
 #> k_m1            0.003835483 6.685819e-03
-#> f_parent_to_m1  0.469113364 5.598386e-01
+#> f_parent_to_m1  0.469113365 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 +313,7 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,
 #> k_parent        TRUE  TRUE
 #> k_m1           FALSE FALSE
 #> f_parent_to_m1  TRUE FALSE
-#> sigma          FALSE  TRUE
signif(rel_diffs_transformed, 3)
#>                    2.5%    97.5%
+#> sigma          FALSE FALSE
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
@@ -327,24 +326,23 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,
 #> sigma          0.055000 0.032700

 
 # Investigate a case with formation fractions
-f_d_2 <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
-ci_profile_ff <- confint(f_d_2, method = "profile", cores = n_cores)
#> Profiling the likelihood
ci_profile_ff
#>                        2.5%        97.5%
+f_d_2 <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
#> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
ci_profile_ff <- confint(f_d_2, method = "profile", cores = n_cores)
#> Profiling the likelihood
ci_profile_ff
#>                        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_ff <- confint(f_d_2, method = "quadratic")
 ci_quadratic_transformed_ff
#>                        2.5%        97.5%
-#> parent_0       96.403839476 1.027931e+02
+#> parent_0       96.403839460 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       96.403839429 1.027931e+02
+#> parent_0       96.403839413 1.027931e+02
 #> k_parent        0.090491931 1.069035e-01
 #> k_m1            0.003835483 6.685819e-03
-#> f_parent_to_m1  0.469113364 5.598386e-01
+#> f_parent_to_m1  0.469113365 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 +354,17 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,
 #> k_parent        TRUE  TRUE
 #> k_m1           FALSE FALSE
 #> f_parent_to_m1  TRUE FALSE
-#> sigma          FALSE  TRUE
rel_diffs_transformed_ff
#>                        2.5%        97.5%
-#> parent_0       0.0005408078 0.0002217796
+#> sigma          FALSE FALSE
rel_diffs_transformed_ff
#>                        2.5%        97.5%
+#> parent_0       0.0005408080 0.0002217794
 #> k_parent       0.0009596417 0.0009003876
-#> 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

+#> 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

 # 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 +373,19 @@ 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)
#> 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
# }
+  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
# }