ind_rhs_calc_nm: Generate individual Right-hand side data (NONMEM)

Description

This functions allows to generate right-hand side data for multiple individuals with individual parameter sets, i.e., combined derivative data of multiple NNs and base-R operations.

Usage

ind_rhs_calc_nm(
  rhs,
  inputs,
  group,
  est_parms = NULL,
  nm_res_file = NULL,
  nm_phi_file = NULL,
  time_nn = NULL,
  act = NULL,
  beta = 20
)

Value

Dataframe with columns for the inputs and the combined right-hand side data.

Arguments

rhs: (string) String of right-hand side
inputs: (dataframe) Dataframe of inputs, with corresponding columns (including matching column names for each variable in rhs.
group: (string) Name of column in inputs dataframe defining groups/individuals.
est_parms: (dataframe; semi-optional) A data frame with estimated individual parameters from the NN extracted through the indparm_extractor_nm function. For optionality, see Details.
nm_res_file: (string; semi-optional) (path)/name of the results file of a NONMEM run, must include file extension, e.g., “.res”. For optionality, see Details.
nm_phi_file: (string; semi-optional) (path)/name of the phi file of a NONMEM run, must include file extension “.phi”. For optionality, see Details.
time_nn: (boolean vector) Vector for each NN in rhs defining whether the neural network is a time-dependent neural network or not. Default value for all NN is FALSE.
act: (character vector) Vector for each NN in rhs defining the activation function used in the NN. Default value for all NN is "ReLU".
beta: (numeric) Beta value for the Softplus activation function, only applicable if any act is softplus; Default to 20.

Author

Dominic Bräm

Details

Either est_parms or nm_res_file and nm_phi_file must be given. If both arguments are given, est_parms is prioritized.