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/nlme.html | 31 ++++++++++++++----------------- 1 file changed, 14 insertions(+), 17 deletions(-) (limited to 'docs/reference/nlme.html') diff --git a/docs/reference/nlme.html b/docs/reference/nlme.html index 3462e52e..85929929 100644 --- a/docs/reference/nlme.html +++ b/docs/reference/nlme.html @@ -43,7 +43,7 @@ +datasets." /> @@ -75,7 +75,7 @@ datasets. They are used internally by the nlme.mmkin() method." /> mkin - 0.9.50.3 + 0.9.50.2 @@ -112,9 +112,6 @@ datasets. They are used internally by the nlme.mmkin() method." />
  • Example evaluation of NAFTA SOP Attachment examples
    • -
  • - Some benchmark timings -
  • @@ -150,7 +147,7 @@ datasets. They are used internally by the nlme.mmkin() method." />

    These functions facilitate setting up a nonlinear mixed effects model for an mmkin row object. An mmkin row object is essentially a list of mkinfit objects that have been obtained by fitting the same model to a list of -datasets. They are used internally by the nlme.mmkin() method.

    +datasets.

    nlme_function(object)
@@ -178,7 +175,7 @@ datasets. They are used internally by the nlme.m
 
    If random is FALSE (default), a named vector containing mean values
 of the fitted degradation model parameters. If random is TRUE, a list with
 fixed and random effects, in the format required by the start argument of
-nlme for the case of a single grouping variable ds.
    
+nlme for the case of a single grouping variable ds?
    
 
    A groupedData object
    
     
    See also
    
 
@@ -225,28 +222,28 @@ nlme for the case of a single grouping variable ds.
    
 #>   Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) 
 #>  Data: grouped_data 
 #>        AIC      BIC    logLik
-#>   298.2781 307.7372 -144.1391
+#>   252.7798 262.1358 -121.3899
 #> 
 #> Random effects:
 #>  Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
 #>  Level: ds
 #>  Structure: Diagonal
-#>          parent_0 log_k_parent_sink Residual
-#> StdDev: 0.9374733         0.7098105  3.83543
+#>            parent_0 log_k_parent_sink Residual
+#> StdDev: 0.004139378         0.6800778 2.489396
 #> 
 #> Fixed effects: parent_0 + log_k_parent_sink ~ 1 
-#>                       Value Std.Error DF  t-value p-value
-#> parent_0          101.76838 1.1445444 45 88.91606       0
-#> log_k_parent_sink  -3.05444 0.4195622 45 -7.28008       0
+#>                       Value Std.Error DF   t-value p-value
+#> parent_0          101.74884 0.6456057 44 157.60213       0
+#> log_k_parent_sink  -3.05575 0.4015812 44  -7.60929       0
 #>  Correlation: 
 #>                   prnt_0
-#> log_k_parent_sink 0.034 
+#> log_k_parent_sink 0.026 
 #> 
 #> Standardized Within-Group Residuals:
-#>        Min         Q1        Med         Q3        Max 
-#> -2.6169360 -0.2185329  0.0574070  0.5720937  3.0459868 
+#>         Min          Q1         Med          Q3         Max 
+#> -2.13168782 -0.68780415  0.08282907  0.85913228  2.95298904 
 #> 
-#> Number of Observations: 49
+#> Number of Observations: 48
 #> Number of Groups: 3 
    plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
    # augPred does not seem to work on fits with more than one state
 # variable
 
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