pmxNODE (version 0.1.0)

nn_parm_setter_nm: Internal: Definition of NN parameters in NONMEM

Description

Define NN parameters consisting of typical parameter and potentially random effects in the $PK section

Usage

nn_parm_setter_nm(
  number,
  pop = FALSE,
  n_hidden = 5,
  eta_model = c("prop", "add"),
  time_nn = FALSE
)

Value

List of parameter definition to be used in the $PK section of the NONMEM model

Arguments

number

(string) Name of the NN, e.g., “1” for NN1(...)

pop

(boolean) Whether population fit without inter-individual variability is performed (TRUE) or whether model is fitted with inter-individual variability (FALSE)

n_hidden

(numeric) Number of neurons in the hidden layer, default value is 5

eta_model

(string)

• “prop” is of form W = lW * EXP(etaW)

• “add” is of form W = lW + etaW

time_nn

(boolean) Whether the neural network to analyze is a time-dependent neural network or not. Default values is FALSE.

Author

Dominic Bräm

Details

eta_model is currently set to proportional as previous investigations showed better stability of fit with this setting in NONMEM