From cf54ccca37d27480dbf8d59eb027300518f7ad75 Mon Sep 17 00:00:00 2001
From: Johannes Ranke Last change 16 January 2018
-(rebuilt 2023-04-20)
+(rebuilt 2023-05-19)
Source: vignettes/web_only/FOCUS_Z.rmd
FOCUS_Z.rmd
plot_sep(m.Z.2a)
-summary(m.Z.2a, data = FALSE)$bpar
summary(m.Z.2a, data = FALSE)$bpar
## Estimate se_notrans t value Pr(>t) Lower Upper
## Z0_0 97.01488 3.301084 29.3888 3.2971e-21 91.66556 102.3642
## k_Z0 2.23601 0.207078 10.7979 3.3309e-11 1.95303 2.5600
@@ -217,7 +217,7 @@ the model formulation:
plot_sep(m.Z.2a.ff)
-summary(m.Z.2a.ff, data = FALSE)$bpar
summary(m.Z.2a.ff, data = FALSE)$bpar
## Estimate se_notrans t value Pr(>t) Lower Upper
## Z0_0 97.01488 3.301084 29.3888 3.2971e-21 91.66556 102.3642
## k_Z0 2.23601 0.207078 10.7979 3.3309e-11 1.95303 2.5600
@@ -247,7 +247,7 @@ previous fit when adding a further metabolite.
plot_sep(m.Z.3)
-summary(m.Z.3, data = FALSE)$bpar
summary(m.Z.3, data = FALSE)$bpar
## Estimate se_notrans t value Pr(>t) Lower Upper
## Z0_0 97.01488 2.597342 37.352 2.0106e-24 91.67597 102.3538
## k_Z0 2.23601 0.146904 15.221 9.1477e-15 1.95354 2.5593
@@ -299,27 +299,27 @@ accelerate the optimization.
plot_sep(m.Z.FOCUS)
-summary(m.Z.FOCUS, data = FALSE)$bpar
summary(m.Z.FOCUS, data = FALSE)$bpar
## Estimate se_notrans t value Pr(>t) Lower Upper
-## Z0_0 96.838822 1.994274 48.5584 4.0280e-42 92.826981 100.850664
-## k_Z0 2.215393 0.118458 18.7019 1.0413e-23 1.989456 2.466989
-## k_Z1 0.478305 0.028258 16.9266 6.2418e-22 0.424708 0.538666
-## k_Z2 0.451627 0.042139 10.7176 1.6314e-14 0.374339 0.544872
-## k_Z3 0.058692 0.015245 3.8499 1.7803e-04 0.034808 0.098965
-## f_Z2_to_Z3 0.471502 0.058351 8.0805 9.6608e-11 0.357769 0.588274
-## sigma 3.984431 0.383402 10.3923 4.5575e-14 3.213126 4.755736
+## Z0_0 96.842440 1.994291 48.5598 4.0226e-42 92.830421 100.854459
+## k_Z0 2.215425 0.118457 18.7023 1.0404e-23 1.989490 2.467019
+## k_Z1 0.478307 0.028257 16.9272 6.2332e-22 0.424709 0.538669
+## k_Z2 0.451642 0.042139 10.7178 1.6304e-14 0.374348 0.544894
+## k_Z3 0.058692 0.015245 3.8499 1.7803e-04 0.034804 0.098975
+## f_Z2_to_Z3 0.471483 0.058348 8.0806 9.6585e-11 0.357720 0.588287
+## sigma 3.984431 0.383402 10.3923 4.5576e-14 3.213126 4.755737
endpoints(m.Z.FOCUS)
## $ff
## Z2_Z3 Z2_sink
-## 0.4715 0.5285
+## 0.47148 0.52852
##
## $distimes
## DT50 DT90
-## Z0 0.31288 1.0394
-## Z1 1.44917 4.8141
-## Z2 1.53478 5.0984
-## Z3 11.80986 39.2315
+## Z0 0.31287 1.0393
+## Z1 1.44917 4.8140
+## Z2 1.53473 5.0983
+## Z3 11.80991 39.2317
This fit corresponds to the final result chosen in Appendix 7 of the FOCUS report. Confidence intervals returned by mkin are based on internally transformed parameters, however.
@@ -350,7 +350,7 @@ improved. However, the covariance matrix is not returned.plot_sep(m.Z.mkin.1)
-summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
## NULL
Therefore, a further stepwise model building is performed starting from the stage of parent and two metabolites, starting from the @@ -442,11 +442,11 @@ obtained.
## ## $SFORB ## Z0_b1 Z0_b2 Z0_g Z3_b1 Z3_b2 Z3_g -## 2.4471322 0.0075125 0.9519862 0.0800069 0.0000000 0.9347820 +## 2.4471342 0.0075124 0.9519866 0.0800071 0.0000000 0.9347816 ## ## $distimes ## DT50 DT90 DT50back DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2 -## Z0 0.3043 1.1848 0.35666 0.28325 92.266 NA NA +## Z0 0.3043 1.1848 0.35666 0.28325 92.267 NA NA ## Z1 1.5148 5.0320 NA NA NA NA NA ## Z2 1.6414 5.4526 NA NA NA NA NA ## Z3 NA NA NA NA NA 8.6636 Inf diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png index 33269a34..c1011a35 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png differ diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png index 6e1877f4..dfd2dd50 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png differ diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png index 113c1b0b..74173f36 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png differ diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png index 6b0dbc34..1c5793cc 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png differ diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png index d080a57a..8c594ec9 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png differ diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png index 3119be2d..84d473d6 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png differ diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png index 1938b499..492cdcc8 100644 Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png differ diff --git a/docs/articles/web_only/NAFTA_examples.html b/docs/articles/web_only/NAFTA_examples.html index 49d1db33..87cef18a 100644 --- a/docs/articles/web_only/NAFTA_examples.html +++ b/docs/articles/web_only/NAFTA_examples.html @@ -33,7 +33,7 @@ @@ -135,7 +135,7 @@ to the US EPA SOP for the NAFTA guidance Rankevignettes/web_only/NAFTA_examples.rmd
NAFTA_examples.rmd
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p5a)
plot(p5a)
print(p5a)
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p5b)
plot(p5b)
print(p5b)
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p6)
plot(p6)
print(p6)
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p7)
plot(p7)
print(p7)
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p8)
plot(p8)
print(p8)
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p9a)
plot(p9a)
print(p9a)
p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
## Warning in sqrt(diag(covar)): NaNs produced
-## Warning in sqrt(diag(covar_notrans)): NaNs produced
-## Warning in sqrt(1/diag(V)): NaNs produced
-## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-
-plot(p9b)
+plot(p9b)
+print(p9b)
## Sums of squares: ## SFO IORE DFOP @@ -526,8 +521,8 @@ suggest a simple exponential decline. ## Estimate Pr(>t) Lower Upper ## parent_0 94.7123 1.61e-16 93.1355 96.2891 ## k1 0.0389 1.08e-04 0.0266 0.0569 -## k2 0.0389 2.23e-04 0.0255 0.0592 -## g 0.5256 NaN NA NA +## k2 0.0389 2.24e-04 0.0255 0.0592 +## g 0.5256 5.00e-01 0.0000 1.0000 ## sigma 1.5957 2.50e-04 0.9135 2.2779 ## ## @@ -549,18 +544,15 @@ in PestDF and g in mkin. In mkin, it is restricted to the interval from
Example on page 10
-+-p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
-## Warning in sqrt(diag(covar)): NaNs produced
-## Warning in sqrt(1/diag(V)): NaNs produced
+## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result -## is doubtful
## Warning in sqrt(diag(covar_notrans)): NaNs produced
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p10)
+plot(p10)
-
+print(p10)
## Sums of squares: ## SFO IORE DFOP @@ -584,12 +576,12 @@ in PestDF and g in mkin. In mkin, it is restricted to the interval from ## sigma 4.90 1.77e-04 2.837 6.968 ## ## $DFOP -## Estimate Pr(>t) Lower Upper -## parent_0 101.7315 1.41e-09 91.6534 111.8097 -## k1 0.0495 6.58e-03 0.0303 0.0809 -## k2 0.0495 2.60e-03 0.0410 0.0598 -## g 0.4487 5.00e-01 NA NA -## sigma 8.0152 2.50e-04 4.5886 11.4418 +## Estimate Pr(>t) Lower Upper +## parent_0 101.7315 1.41e-09 91.6534 111.810 +## k1 0.0495 3.04e-03 0.0188 0.131 +## k2 0.0495 4.92e-04 0.0197 0.124 +## g 0.4487 NaN 0.0000 1.000 +## sigma 8.0152 2.50e-04 4.5886 11.442 ## ## ## DTx values: @@ -613,14 +605,14 @@ difference in IORE model parameters between PestDF and mkin.
Example on page 11
-+p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p11)
+plot(p11)
-
+print(p11)
+## [1] 41148169## Sums of squares: ## SFO IORE DFOP @@ -659,7 +651,7 @@ difference in IORE model parameters between PestDF and mkin. ## DFOP 3.07e+11 1.93e+12 6.98e+11 ## ## Representative half-life: -## [1] 41148170
In this case, the DFOP fit reported for PestDF resulted in a negative value for the slower rate constant, which is not possible in mkin. The other results are in agreement.
@@ -676,21 +668,17 @@ overparameterisation.Example on page 12, upper panel
--- cgit v1.2.1+p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
-## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance ## matrix
## Warning in sqrt(diag(covar)): NaNs produced
-## Warning in sqrt(diag(covar_notrans)): NaNs produced
-## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result -## is doubtful
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p12a)
+plot(p12a)
-
@@ -600,6 +628,13 @@ systems. All trademarks belong to their respective owners.+print(p12a)
## Sums of squares: ## SFO IORE DFOP @@ -718,7 +706,7 @@ overparameterisation. ## parent_0 100.521 2.74e-10 92.2366 108.805 ## k1 0.124 2.53e-05 0.0908 0.170 ## k2 0.124 2.52e-02 0.0456 0.339 -## g 0.793 NaN NA NA +## g 0.793 NaN 0.0000 1.000 ## sigma 7.048 2.50e-04 4.0349 10.061 ## ## @@ -734,18 +722,21 @@ overparameterisation.
@@ -542,6 +562,14 @@ systems. All trademarks belong to their respective owners.Example on page 12, lower panel
-++p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
## Warning in sqrt(diag(covar)): NaNs produced
## Warning in qt(alpha/2, rdf): NaNs produced
-## Warning in qt(1 - alpha/2, rdf): NaNs produced
## Warning in sqrt(diag(covar_notrans)): NaNs produced
+## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
+## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result +## is doubtful
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p12b)
+plot(p12b)
-
+print(p12b)
## Sums of squares: ## SFO IORE DFOP @@ -789,14 +780,14 @@ overparameterisation.
Example on page 13
-+p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p13)
+plot(p13)
-
+print(p13)
## Sums of squares: ## SFO IORE DFOP @@ -822,8 +813,8 @@ overparameterisation. ## $DFOP ## Estimate Pr(>t) Lower Upper ## parent_0 92.73500 NA 8.95e+01 95.92118 -## k1 0.00258 NA 4.14e-04 0.01611 -## k2 0.00258 NA 1.74e-03 0.00383 +## k1 0.00258 NA 4.18e-04 0.01592 +## k2 0.00258 NA 1.75e-03 0.00381 ## g 0.16452 NA 0.00e+00 1.00000 ## sigma 3.41172 NA 2.02e+00 4.79960 ## @@ -841,7 +832,7 @@ overparameterisation.
DT50 not observed in the study and DFOP problems in PestDF
-+p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
## Warning in sqrt(diag(covar)): NaNs produced
@@ -849,10 +840,10 @@ overparameterisation. ## is doubtful## Warning in sqrt(1/diag(V)): NaNs produced
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p14)
+plot(p14)
-
@@ -135,7 +135,7 @@ from 2018 Ranke++print(p14)
@@ -899,14 +890,18 @@ same results in mkin and PestDF.## Sums of squares: ## SFO IORE DFOP @@ -879,7 +870,7 @@ overparameterisation. ## Estimate Pr(>t) Lower Upper ## parent_0 1.00e+02 2.96e-28 99.40280 101.2768 ## k1 9.53e-03 1.20e-01 0.00638 0.0143 -## k2 6.08e-12 5.00e-01 0.00000 Inf +## k2 5.21e-12 5.00e-01 0.00000 Inf ## g 3.98e-01 2.19e-01 0.30481 0.4998 ## sigma 1.17e+00 7.68e-06 0.77406 1.5610 ## @@ -888,7 +879,7 @@ overparameterisation. ## DT50 DT90 DT50_rep ## SFO 2.48e+02 8.25e+02 2.48e+02 ## IORE 4.34e+02 2.22e+04 6.70e+03 -## DFOP 3.05e+10 2.95e+11 1.14e+11 +## DFOP 3.55e+10 3.44e+11 1.33e+11 ## ## Representative half-life: ## [1] 6697.44
N is less than 1 and DFOP fraction parameter is below zero
-@@ -247,12 +247,12 @@ compiled code is available. }++p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
+## Warning in sqrt(diag(covar)): NaNs produced
+## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result +## is doubtful
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p15a)
+plot(p15a)
-
+print(p15a)
-## Sums of squares: ## SFO IORE DFOP @@ -932,9 +927,9 @@ same results in mkin and PestDF. ## $DFOP ## Estimate Pr(>t) Lower Upper ## parent_0 97.96751 2.85e-13 94.21913 101.7159 -## k1 0.00952 6.28e-02 0.00250 0.0363 -## k2 0.00952 1.27e-04 0.00646 0.0140 -## g 0.21241 5.00e-01 0.00000 1.0000 +## k1 0.00952 6.28e-02 0.00260 0.0349 +## k2 0.00952 1.27e-04 0.00652 0.0139 +## g 0.21241 5.00e-01 NA NA ## sigma 4.18778 2.50e-04 2.39747 5.9781 ## ## @@ -946,18 +941,16 @@ same results in mkin and PestDF. ## ## Representative half-life: ## [1] 41.33
@@ -134,7 +134,7 @@ definitions in mkin+-p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
-## Warning in sqrt(diag(covar)): NaNs produced
-## Warning in sqrt(1/diag(V)): NaNs produced
+## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result -## is doubtful
## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance +## matrix
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+-plot(p15b)
+plot(p15b)
-
diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html index a411dad1..3c53b40a 100644 --- a/docs/articles/web_only/compiled_models.html +++ b/docs/articles/web_only/compiled_models.html @@ -33,7 +33,7 @@+print(p15b)
## Sums of squares: ## SFO IORE DFOP @@ -975,18 +968,18 @@ same results in mkin and PestDF. ## ## $IORE ## Estimate Pr(>t) Lower Upper -## parent_0 99.83 1.81e-16 97.51349 102.14 +## parent_0 99.83 1.81e-16 97.51348 102.14 ## k__iore_parent 0.38 3.22e-01 0.00352 41.05 ## N_parent 0.00 5.00e-01 -1.07696 1.08 ## sigma 2.21 2.57e-04 1.23245 3.19 ## ## $DFOP -## Estimate Pr(>t) Lower Upper -## parent_0 1.01e+02 NA 9.82e+01 1.04e+02 -## k1 4.86e-03 NA 8.63e-04 2.73e-02 -## k2 4.86e-03 NA 3.21e-03 7.35e-03 -## g 1.88e-01 NA NA NA -## sigma 2.76e+00 NA 1.58e+00 3.94e+00 +## Estimate Pr(>t) Lower Upper +## parent_0 1.01e+02 NA NA NA +## k1 4.86e-03 NA NA NA +## k2 4.86e-03 NA NA NA +## g 1.88e-01 NA NA NA +## sigma 2.76e+00 NA NA NA ## ## ## DTx values: @@ -1005,16 +998,16 @@ mkin and PestDF.
@@ -963,6 +980,18 @@ dataset, i.e. one fit for each test.The DFOP fraction parameter is greater than 1
-@@ -652,6 +660,15 @@ for each test.+p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The representative half-life of the IORE model is longer than the one corresponding
## to the terminal degradation rate found with the DFOP model.
-## The representative half-life obtained from the DFOP model may be used
+-plot(p16)
+plot(p16)
-
@@ -134,7 +134,7 @@ Ranke+print(p16)
## Sums of squares: ## SFO IORE DFOP diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png index 566625ea..1d4a25e0 100644 Binary files a/docs/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png and b/docs/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png differ diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png index b5fd7d91..aa55169e 100644 Binary files a/docs/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png and b/docs/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png differ diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p15b-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p15b-1.png index dfbc996f..d17c7aae 100644 Binary files a/docs/articles/web_only/NAFTA_examples_files/figure-html/p15b-1.png and b/docs/articles/web_only/NAFTA_examples_files/figure-html/p15b-1.png differ diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p5b-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p5b-1.png index 6fd175cb..9e38e696 100644 Binary files a/docs/articles/web_only/NAFTA_examples_files/figure-html/p5b-1.png and b/docs/articles/web_only/NAFTA_examples_files/figure-html/p5b-1.png differ diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p6-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p6-1.png index 856c6778..e6e3abbe 100644 Binary files a/docs/articles/web_only/NAFTA_examples_files/figure-html/p6-1.png and b/docs/articles/web_only/NAFTA_examples_files/figure-html/p6-1.png differ diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png index b078fb88..7c5d4bab 100644 Binary files a/docs/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png and b/docs/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png differ diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html index 3e73bd12..315ad54e 100644 --- a/docs/articles/web_only/benchmarks.html +++ b/docs/articles/web_only/benchmarks.html @@ -33,7 +33,7 @@
Last change 17 February 2023 -(rebuilt 2023-04-20)
+(rebuilt 2023-05-19) Source:vignettes/web_only/benchmarks.rmd
@@ -425,6 +425,14 @@ models fitted to two datasets, i.e. eight fits for each test.benchmarks.rmd
1.406 1.948 ++ Linux +Ryzen 9 7950X +4.3.0 +1.2.4 +1.386 +1.960 +2.109 1.178 ++ Linux +Ryzen 9 7950X +4.3.0 +1.2.4 +0.779 +2.080 +1.106 +0.743 0.989 ++ Linux +Ryzen 9 7950X +4.3.0 +1.2.4 +0.410 +0.526 +0.553 +1.249 +0.712 +0.948 +Johannes Ranke
-2023-04-20
+2023-05-19
Source:vignettes/web_only/compiled_models.rmd
@@ -213,10 +213,10 @@ solution is also implemented, which is included in the tests below. print("R package rbenchmark is not available") }compiled_models.rmd
+## 4 analytical 1 1.000 0.099 +## 3 deSolve, compiled 1 1.303 0.129 +## 2 Eigenvalue based 1 1.697 0.168 +## 1 deSolve, not compiled 1 21.475 2.126## test replications relative elapsed -## 4 analytical 1 1.000 0.103 -## 3 deSolve, compiled 1 1.291 0.133 -## 2 Eigenvalue based 1 1.718 0.177 -## 1 deSolve, not compiled 1 22.136 2.280
We see that using the compiled model is by more than a factor of 10 faster than using deSolve without compiled code.
## Temporary DLL for differentials generated and loaded
-## test replications relative elapsed -## 2 deSolve, compiled 1 1.000 0.171 -## 1 deSolve, not compiled 1 24.199 4.138
Here we get a performance benefit of a factor of 24 using the version +## 2 deSolve, compiled 1 1.000 0.165 +## 1 deSolve, not compiled 1 22.673 3.741
Here we get a performance benefit of a factor of 23 using the version of the differential equation model compiled from C code!
-This vignette was built with mkin 1.2.3 on
-## R version 4.2.3 (2023-03-15) +
This vignette was built with mkin 1.2.4 on
+## R version 4.3.0 Patched (2023-05-18 r84448) ## Platform: x86_64-pc-linux-gnu (64-bit) ## Running under: Debian GNU/Linux 12 (bookworm)
diff --git a/docs/articles/web_only/dimethenamid_2018.html b/docs/articles/web_only/dimethenamid_2018.html index 4575067b..a89631a2 100644 --- a/docs/articles/web_only/dimethenamid_2018.html +++ b/docs/articles/web_only/dimethenamid_2018.html @@ -33,7 +33,7 @@## CPU model: AMD Ryzen 9 7950X 16-Core Processor
Last change 1 July 2022, -built on 20 Apr 2023
+built on 19 May 2023 Source:vignettes/web_only/dimethenamid_2018.rmd
@@ -222,12 +222,12 @@ least in some datasets the degradation slows down towards later time points, and that the scatter of the residuals error is smaller for smaller values (panel to the right): +dimethenamid_2018.rmd
plot(mixed(f_parent_mkin_const["SFO", ]))
Using biexponential decline (DFOP) results in a slightly more random scatter of the residuals:
+plot(mixed(f_parent_mkin_const["DFOP", ]))
The population curve (bold line) in the above plot results from taking the mean of the individual transformed parameters, i.e. of log k1 @@ -239,7 +239,7 @@ dominates the average. This is alleviated if only rate constants that pass the t-test for significant difference from zero (on the untransformed scale) are considered in the averaging:
+plot(mixed(f_parent_mkin_const["DFOP", ]), test_log_parms = TRUE)
While this is visually much more satisfactory, such an average procedure could introduce a bias, as not all results from the individual @@ -251,7 +251,7 @@ degradation model and the error model (see below).
predicted residues is reduced by using the two-component error model: +plot(mixed(f_parent_mkin_tc["DFOP", ]), test_log_parms = TRUE)
However, note that in the case of using this error model, the fits to the Flaach and BBA 2.3 datasets appear to be ill-defined, indicated by @@ -341,7 +341,7 @@ effects does not improve the fits.
The selected model (DFOP with two-component error) fitted to the data assuming no correlations between random effects is shown below.
+-plot(f_parent_nlme_dfop_tc)
plot(f_parent_nlme_dfop_tc)
@@ -549,7 +549,7 @@ iterations second phase, 15 chains). saemix_is = sapply(list(f_parent_saemix_sfo_const$so, f_parent_saemix_sfo_tc$so, f_parent_saemix_dfop_const$so, f_parent_saemix_dfop_tc$so), AIC, method = "is") ) -kable(AIC_all)+kable(AIC_all)
Degradation model @@ -614,13 +614,13 @@ satisfactory precision. -R version 4.2.3 (2023-03-15) +
+ [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 saemix_3.2 + [5] stringi_1.7.12 lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 + [9] evaluate_0.21 grid_4.3.0 fastmap_1.1.1 rprojroot_2.0.3 +[13] jsonlite_1.8.4 DBI_1.1.3 mclust_6.0.0 gridExtra_2.3 +[17] purrr_1.0.1 fansi_1.0.4 scales_1.2.1 textshaping_0.3.6 +[21] jquerylib_0.1.4 cli_3.6.1 rlang_1.1.1 munsell_0.5.0 +[25] cachem_1.0.8 yaml_2.3.7 tools_4.3.0 parallel_4.3.0 +[29] memoise_2.0.1 dplyr_1.1.2 colorspace_2.1-0 ggplot2_3.4.2 +[33] vctrs_0.6.2 R6_2.5.1 zoo_1.8-12 lifecycle_1.0.3 +[37] stringr_1.5.0 fs_1.6.2 ragg_1.2.5 pkgconfig_2.0.3 +[41] desc_1.4.2 pkgdown_2.0.7 bslib_0.4.2 pillar_1.9.0 +[45] gtable_0.3.3 glue_1.6.2 systemfonts_1.0.4 xfun_0.39 +[49] tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 npde_3.3 +[53] htmltools_0.5.5 rmarkdown_2.21 compiler_4.3.0R version 4.3.0 Patched (2023-05-18 r84448) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default -BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3 -LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so +BLAS: /home/jranke/svn/R/r-patched/build/lib/libRblas.so +LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/liblapack.so.3; LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -630,27 +630,30 @@ locale: [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C +time zone: Europe/Berlin +tzcode source: system (glibc) + attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: -[1] saemix_3.2 npde_3.3 nlme_3.1-162 mkin_1.2.3 knitr_1.42 +[1] nlme_3.1-162 mkin_1.2.4 knitr_1.42 loaded via a namespace (and not attached): - [1] highr_0.10 pillar_1.9.0 bslib_0.4.2 compiler_4.2.3 - [5] jquerylib_0.1.4 tools_4.2.3 mclust_6.0.0 digest_0.6.31 - [9] tibble_3.2.1 jsonlite_1.8.4 evaluate_0.20 memoise_2.0.1 -[13] lifecycle_1.0.3 gtable_0.3.3 lattice_0.21-8 pkgconfig_2.0.3 -[17] rlang_1.1.0 DBI_1.1.3 cli_3.6.1 yaml_2.3.7 -[21] parallel_4.2.3 pkgdown_2.0.7 xfun_0.38 fastmap_1.1.1 -[25] gridExtra_2.3 dplyr_1.1.1 stringr_1.5.0 generics_0.1.3 -[29] desc_1.4.2 fs_1.6.1 vctrs_0.6.1 sass_0.4.5 -[33] systemfonts_1.0.4 tidyselect_1.2.0 rprojroot_2.0.3 lmtest_0.9-40 -[37] grid_4.2.3 glue_1.6.2 R6_2.5.1 textshaping_0.3.6 -[41] fansi_1.0.4 rmarkdown_2.21 purrr_1.0.1 ggplot2_3.4.2 -[45] magrittr_2.0.3 codetools_0.2-19 scales_1.2.1 htmltools_0.5.5 -[49] colorspace_2.1-0 ragg_1.2.5 utf8_1.2.3 stringi_1.7.12 -[53] munsell_0.5.0 cachem_1.0.7 zoo_1.8-12
@@ -134,7 +134,7 @@ RankeReferences diff --git a/docs/articles/web_only/multistart.html b/docs/articles/web_only/multistart.html index 04093e82..b9224bb0 100644 --- a/docs/articles/web_only/multistart.html +++ b/docs/articles/web_only/multistart.html @@ -33,7 +33,7 @@
Last change 20 April 2023 -(rebuilt 2023-04-20)
+(rebuilt 2023-05-19) Source:vignettes/web_only/multistart.rmd
@@ -175,7 +175,7 @@ assessment using multiple runs with different starting values. parameter, so we reduce the parameter distribution model by removing the intersoil variability for k2.multistart.rmd
@@ -190,18 +190,20 @@ runs:-f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") +
f_saem_reduced <- stats::update(f_saem_full, no_random_effect = "log_k2") illparms(f_saem_reduced) f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cores = 16) parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2))
We can use the
+ f_saem_reduced, best(f_saem_reduced_multi), test = TRUE)anova
method to compare the models.-## Data: 155 observations of 1 variable(s) grouped in 6 datasets ## -## npar AIC BIC Lik -## f_saem_reduced 9 663.73 661.86 -322.86 -## best(f_saem_reduced_multi) 9 663.69 661.82 -322.85 -## f_saem_full 10 669.77 667.69 -324.89 -## best(f_saem_full_multi) 10 665.56 663.48 -322.78
The reduced model gives the lowest information criteria and similar -likelihoods as the best variant of the full model. The multistart method -leads to a much lower improvement of the likelihood for the reduced -model, indicating that it converges faster.
+## npar AIC BIC Lik Chisq Df Pr(>Chisq) +## f_saem_reduced 9 663.67 661.80 -322.84 +## best(f_saem_reduced_multi) 9 663.65 661.78 -322.82 0.0219 0 +## f_saem_full 10 670.09 668.01 -325.05 0.0000 1 1 +## best(f_saem_full_multi) 10 665.61 663.52 -322.80 4.4870 0 +The reduced model results in lower AIC and BIC values, so it is +clearly preferable. Using multiple starting values gives a large +improvement in case of the full model, because it is less well-defined, +which impedes convergence. For the reduced model, using multiple +starting values only results in a small improvement of the model +fit.
@@ -134,7 +134,7 @@ RankeLast change 17 February 2023 -(rebuilt 2023-04-20)
+(rebuilt 2023-05-19) Source:vignettes/web_only/saem_benchmarks.rmd
@@ -238,22 +238,22 @@ explanation of the following preprocessing.saem_benchmarks.rmd
dfop_tc 10 -669.8 -667.7 --324.9 +670.1 +668.0 +-325.0 sforb_tc 10 -662.8 -660.7 +662.9 +660.8 -321.4 @@ -402,6 +402,16 @@ systems. All trademarks belong to their respective owners. hs_tc 10 -667.3 -665.2 +667.2 +665.1 -323.6 1.926 2.398 ++ Ryzen 9 7950X +Linux +1.2.4 +3.2 +0.972 +2.550 +1.987 +2.055 +Two-component error fits for SFO, DFOP, SFORB and HS.
@@ -477,6 +487,16 @@ systems. All trademarks belong to their respective owners.3.253 3.530 ++ Ryzen 9 7950X +Linux +1.2.4 +3.2 +2.127 +3.587 +3.433 +3.595 +12.841 292.688 ++ Ryzen 9 7950X +Linux +1.2.4 +3.2 +12.160 +265.934 +3.2 483.027 ++ Ryzen 9 7950X +Linux +1.2.4 +3.2 +456.252 +