From 8b7edd4eaf0d196e674a085f744d1a69260a6c91 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 16 Nov 2023 06:02:05 +0100 Subject: Update pkgdown docs to bootstrap 5 with search --- docs/reference/saem.html | 208 ++++++++++++++++++++--------------------------- 1 file changed, 86 insertions(+), 122 deletions(-) (limited to 'docs/reference/saem.html') diff --git a/docs/reference/saem.html b/docs/reference/saem.html index 527718ef..b295ab64 100644 --- a/docs/reference/saem.html +++ b/docs/reference/saem.html @@ -1,122 +1,90 @@ -Fit nonlinear mixed models with SAEM — saem • mkinFit nonlinear mixed models with SAEM — saem • mkin + + Skip to contents -
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This function uses saemix::saemix() as a backend for fitting nonlinear mixed effects models created from mmkin row objects using the Stochastic Approximation Expectation Maximisation algorithm (SAEM).

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Usage

saem(object, ...)
 
 # S3 method for mmkin
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saemix_data(object, covariates = NULL, verbose = FALSE, ...)
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Arguments

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Arguments

object

An mmkin row object containing several fits of the same mkinmod model to different datasets

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Number of digits to use for printing

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Value

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Value

An S3 object of class 'saem.mmkin', containing the fitted @@ -289,21 +257,21 @@ object also inherits from 'mixed.mmkin'.

An saemix::SaemixData object.

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Details

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Details

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 using mkinfit.

Starting values for the fixed effects (population mean parameters, argument psi0 of saemix::saemixModel() are the mean values of the parameters found using mmkin.

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See also

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Examples

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Examples

# \dontrun{
 ds <- lapply(experimental_data_for_UBA_2019[6:10],
  function(x) subset(x$data[c("name", "time", "value")]))
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summary(f_saem_dfop_sfo, data = TRUE) #> saemix version used for fitting: 3.2 #> mkin version used for pre-fitting: 1.2.6 -#> R version used for fitting: 4.3.1 -#> Date of fit: Mon Oct 30 09:34:35 2023 -#> Date of summary: Mon Oct 30 09:34:35 2023 +#> R version used for fitting: 4.3.2 +#> Date of fit: Thu Nov 16 04:17:34 2023 +#> Date of summary: Thu Nov 16 04:17:34 2023 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -462,7 +430,7 @@ using mmkin.

#> #> Model predictions using solution type analytical #> -#> Fitted in 8.745 s +#> Fitted in 3.385 s #> Using 300, 100 iterations and 10 chains #> #> Variance model: Constant variance @@ -758,26 +726,22 @@ using mmkin.

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