nn_theta_def_mlx

Get parameter names for one specific NN in the model, i.e., weight and bias names

internal

An easy-to-use tool for implementing Neural Ordinary Differential Equations (NODEs) in pharmacometric software such as 'Monolix', 'NONMEM', and 'nlmixr2', see Bräm et al. (2024) <doi:10.1007/s10928-023-09886-4> and Bräm et al. (2025) <doi:10.1002/psp4.13265>. The main functionality is to automatically generate structural model code describing computations within a neural network. Additionally, parameters and software settings can be initialized automatically. For using these additional functionalities with 'Monolix', 'pmxNODE' interfaces with 'MonolixSuite' via the 'lixoftConnectors' package. The 'lixoftConnectors' package is distributed with 'MonolixSuite' (<https://monolixsuite.slp-software.com/r-functions/2024R1/package-lixoftconnectors>) and is not available from public repositories.

Dominic Bräm

pmxNODE

Application of NODEs in 'Monolix', 'NONMEM', and 'nlmixr2'

Bernhard Steiert

Gilbert Koch

Matthew Fidler

nn_theta_def_mlx function

<dl><dt>number</dt>
<dd>(string) Name of the NN, e.g., &#8220;1&#8221; for NN1(...)</dd>
<dt>n_hidden</dt>
<dd>(numeric) Number of neurons in the hidden layer, default value is 5</dd>
<dt>time_nn</dt>
<dd>(boolean) Whether the neural network to analyze is a time-dependent neural network or not. Default values is FALSE.</dd></dl>

Arguments

Author

Internal: Define NN parameters names — nn_theta_def_mlx

<dl>

<dt>number</dt>
<dd>(string) Name of the NN, e.g., &#8220;1&#8221; for NN1(...)</dd>


<dt>n_hidden</dt>
<dd>(numeric) Number of neurons in the hidden layer, default value is 5</dd>


<dt>time_nn</dt>
<dd>(boolean) Whether the neural network to analyze is a time-dependent neural network or not. Default values is FALSE.</dd>

</dl>

nn_theta_def_mlx: Internal: Define NN parameters names

Description

Usage

Value

Arguments

Author