From 91c5db736a4d3f2290a0cc5698fb4e35ae7bda59 Mon Sep 17 00:00:00 2001
From: Johannes Ranke
Date: Wed, 18 May 2022 21:26:17 +0200
Subject: Remove outdated comment in FOCUS L vignette, update docs
This also adds the first benchmark results obtained on my laptop system
---
docs/reference/dimethenamid_2018.html | 92 +++++++++++++++++------------------
1 file changed, 46 insertions(+), 46 deletions(-)
(limited to 'docs/reference/dimethenamid_2018.html')
diff --git a/docs/reference/dimethenamid_2018.html b/docs/reference/dimethenamid_2018.html
index d2ed8647..a3cfc271 100644
--- a/docs/reference/dimethenamid_2018.html
+++ b/docs/reference/dimethenamid_2018.html
@@ -202,9 +202,9 @@ specific pieces of information in the comments.
summary(f_dmta_saem_tc)
#> saemix version used for fitting: 3.0
#> mkin version used for pre-fitting: 1.1.0
-#> R version used for fitting: 4.1.3
-#> Date of fit: Sat Apr 9 18:03:34 2022
-#> Date of summary: Sat Apr 9 18:03:34 2022
+#> R version used for fitting: 4.2.0
+#> Date of fit: Wed May 18 20:37:14 2022
+#> Date of summary: Wed May 18 20:37:14 2022
#>
#> Equations:
#> d_DMTA/dt = - k_DMTA * DMTA
@@ -217,7 +217,7 @@ specific pieces of information in the comments.
#>
#> Model predictions using solution type deSolve
#>
-#> Fitted in 787.836 s
+#> Fitted in 1660.941 s
#> Using 300, 100 iterations and 9 chains
#>
#> Variance model: Two-component variance function
@@ -239,65 +239,65 @@ specific pieces of information in the comments.
#>
#> Optimised parameters:
#> est. lower upper
-#> DMTA_0 88.5943 84.3961 92.7925
-#> log_k_DMTA -3.0466 -3.5609 -2.5322
-#> log_k_M23 -4.0684 -4.9340 -3.2029
-#> log_k_M27 -3.8628 -4.2627 -3.4628
-#> log_k_M31 -3.9803 -4.4804 -3.4801
-#> f_DMTA_ilr_1 0.1304 -0.2186 0.4795
-#> f_DMTA_ilr_2 0.1490 -0.2559 0.5540
-#> f_DMTA_ilr_3 -1.3970 -1.6976 -1.0964
+#> DMTA_0 88.3098 84.1383 92.4813
+#> log_k_DMTA -3.0510 -3.5659 -2.5361
+#> log_k_M23 -4.0567 -4.9178 -3.1955
+#> log_k_M27 -3.8592 -4.2571 -3.4614
+#> log_k_M31 -3.9685 -4.4683 -3.4686
+#> f_DMTA_ilr_1 0.1382 -0.2120 0.4885
+#> f_DMTA_ilr_2 0.1429 -0.2616 0.5473
+#> f_DMTA_ilr_3 -1.3889 -1.6943 -1.0836
#>
#> Correlation:
#> DMTA_0 l__DMTA lg__M23 lg__M27 lg__M31 f_DMTA__1 f_DMTA__2
-#> log_k_DMTA 0.0309
-#> log_k_M23 -0.0231 -0.0031
-#> log_k_M27 -0.0381 -0.0048 0.0039
-#> log_k_M31 -0.0251 -0.0031 0.0021 0.0830
-#> f_DMTA_ilr_1 -0.0046 -0.0006 0.0417 -0.0437 0.0328
-#> f_DMTA_ilr_2 -0.0008 -0.0002 0.0214 -0.0270 -0.0909 -0.0361
-#> f_DMTA_ilr_3 -0.1832 -0.0135 0.0434 0.0804 0.0395 -0.0070 0.0059
+#> log_k_DMTA 0.0315
+#> log_k_M23 -0.0237 -0.0031
+#> log_k_M27 -0.0392 -0.0048 0.0040
+#> log_k_M31 -0.0257 -0.0032 0.0022 0.0821
+#> f_DMTA_ilr_1 -0.0048 -0.0007 0.0415 -0.0435 0.0333
+#> f_DMTA_ilr_2 -0.0007 -0.0002 0.0214 -0.0270 -0.0900 -0.0372
+#> f_DMTA_ilr_3 -0.1861 -0.0136 0.0431 0.0797 0.0382 -0.0072 0.0066
#>
#> Random effects:
#> est. lower upper
-#> SD.DMTA_0 3.3651 -0.9655 7.6956
-#> SD.log_k_DMTA 0.6415 0.2774 1.0055
-#> SD.log_k_M23 1.0176 0.3809 1.6543
-#> SD.log_k_M27 0.4538 0.1522 0.7554
-#> SD.log_k_M31 0.5684 0.1905 0.9464
-#> SD.f_DMTA_ilr_1 0.4111 0.1524 0.6699
-#> SD.f_DMTA_ilr_2 0.4788 0.1808 0.7768
-#> SD.f_DMTA_ilr_3 0.3501 0.1316 0.5685
+#> SD.DMTA_0 3.2733 -1.1098 7.6564
+#> SD.log_k_DMTA 0.6422 0.2777 1.0066
+#> SD.log_k_M23 1.0131 0.3797 1.6465
+#> SD.log_k_M27 0.4511 0.1510 0.7513
+#> SD.log_k_M31 0.5695 0.1923 0.9466
+#> SD.f_DMTA_ilr_1 0.4123 0.1526 0.6720
+#> SD.f_DMTA_ilr_2 0.4780 0.1804 0.7757
+#> SD.f_DMTA_ilr_3 0.3559 0.1344 0.5775
#>
#> Variance model:
#> est. lower upper
-#> a.1 0.9349 0.8395 1.0302
-#> b.1 0.1344 0.1176 0.1512
+#> a.1 0.9255 0.8288 1.0221
+#> b.1 0.1365 0.1191 0.1538
#>
#> Backtransformed parameters:
#> est. lower upper
-#> DMTA_0 88.59431 84.396147 92.79246
-#> k_DMTA 0.04752 0.028413 0.07948
-#> k_M23 0.01710 0.007198 0.04064
-#> k_M27 0.02101 0.014084 0.03134
-#> k_M31 0.01868 0.011329 0.03080
-#> f_DMTA_to_M23 0.14498 NA NA
-#> f_DMTA_to_M27 0.12056 NA NA
-#> f_DMTA_to_M31 0.11015 NA NA
+#> DMTA_0 88.30980 84.138334 92.48126
+#> k_DMTA 0.04731 0.028272 0.07918
+#> k_M23 0.01731 0.007315 0.04095
+#> k_M27 0.02108 0.014164 0.03139
+#> k_M31 0.01890 0.011467 0.03116
+#> f_DMTA_to_M23 0.14626 NA NA
+#> f_DMTA_to_M27 0.12029 NA NA
+#> f_DMTA_to_M31 0.11135 NA NA
#>
#> Resulting formation fractions:
#> ff
-#> DMTA_M23 0.1450
-#> DMTA_M27 0.1206
-#> DMTA_M31 0.1101
-#> DMTA_sink 0.6243
+#> DMTA_M23 0.1463
+#> DMTA_M27 0.1203
+#> DMTA_M31 0.1113
+#> DMTA_sink 0.6221
#>
#> Estimated disappearance times:
#> DT50 DT90
-#> DMTA 14.59 48.45
-#> M23 40.52 134.62
-#> M27 32.99 109.60
-#> M31 37.11 123.26
+#> DMTA 14.65 48.67
+#> M23 40.05 133.05
+#> M27 32.88 109.21
+#> M31 36.67 121.81
# As the confidence interval for the random effects of DMTA_0
# includes zero, we could try an alternative model without
# such random effects
@@ -321,7 +321,7 @@ specific pieces of information in the comments.
--
cgit v1.2.1