From 630e657f1794ea441afc9ff10663309fec5e847e Mon Sep 17 00:00:00 2001
From: Johannes Ranke
Date: Tue, 1 Nov 2022 14:16:21 +0100
Subject: Update online docs
---
docs/dev/reference/saem.html | 18 ++++++++++++------
1 file changed, 12 insertions(+), 6 deletions(-)
(limited to 'docs/dev/reference/saem.html')
diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html
index c8a7504f..8ea0ef6e 100644
--- a/docs/dev/reference/saem.html
+++ b/docs/dev/reference/saem.html
@@ -19,7 +19,7 @@ Expectation Maximisation algorithm (SAEM).">
mkin
- 1.1.2
+ 1.2.0
@@ -100,6 +100,7 @@ Expectation Maximisation algorithm (SAEM).
saem(
object,
transformations = c("mkin", "saemix"),
+ error_model = "auto",
degparms_start = numeric(),
test_log_parms = TRUE,
conf.level = 0.6,
@@ -124,6 +125,7 @@ Expectation Maximisation algorithm (SAEM).
object,
solution_type = "auto",
transformations = c("mkin", "saemix"),
+ error_model = "auto",
degparms_start = numeric(),
covariance.model = "auto",
no_random_effect = NULL,
@@ -160,6 +162,10 @@ SFO, FOMC, DFOP and HS without fixing parent_0
, and SFO or DFOP wit
one SFO metabolite.
+error_model
+Possibility to override the error model used in the mmkin object
+
+
degparms_start
Parameter values given as a named numeric vector will
be used to override the starting values obtained from the 'mmkin' object.
@@ -409,10 +415,10 @@ using mmkin.
summary(f_saem_dfop_sfo, data = TRUE)
#> saemix version used for fitting: 3.2
-#> mkin version used for pre-fitting: 1.1.2
-#> R version used for fitting: 4.2.1
-#> Date of fit: Wed Oct 26 09:20:37 2022
-#> Date of summary: Wed Oct 26 09:20:37 2022
+#> mkin version used for pre-fitting: 1.2.0
+#> R version used for fitting: 4.2.2
+#> Date of fit: Tue Nov 1 14:12:07 2022
+#> Date of summary: Tue Nov 1 14:12:07 2022
#>
#> Equations:
#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -427,7 +433,7 @@ using mmkin.
#>
#> Model predictions using solution type analytical
#>
-#> Fitted in 8.902 s
+#> Fitted in 8.45 s
#> Using 300, 100 iterations and 10 chains
#>
#> Variance model: Constant variance
--
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