set_combined_error_model: set_combined_error_model

In pharmpy/pharmr: Interface to the 'Pharmpy' 'Pharmacometrics' Library

set_combined_error_model

Description

Set a combined error model. Initial estimates for new sigmas are (equation could not be rendered, see API doc on website) proportional and 0.09 for additive.

The error function being applied depends on the data transformation.

+————————+—————————————————–+ | Data transformation | Combined error | +========================+=====================================================+ | (equation could not be rendered, see API doc on website) +————————+—————————————————–+ | (equation could not be rendered, see API doc on website) +————————+—————————————————–+

Usage

set_combined_error_model(model, dv = NULL, data_trans = NULL)

Arguments

model	(Model) Set error model for this model
dv	(Expr or str or numeric (optional)) Name or DVID of dependent variable. NULL for the default (first or only)
data_trans	(numeric or str or Expr (optional)) A data transformation expression or NULL (default) to use the transformation specified by the model.

Value

(Model) Pharmpy model object

See Also

set_additive_error_model : Additive error model

set_proportional_error_model: Proportional error model

Examples

## Not run: 
model <- remove_error_model(load_example_model("pheno"))
model <- set_combined_error_model(model)
model$statements$find_assignment("Y")
model <- remove_error_model(load_example_model("pheno"))
model <- set_combined_error_model(model, data_trans="log(Y)")
model$statements$find_assignment("Y")

## End(Not run)

pharmpy/pharmr documentation built on Feb. 15, 2025, 3:22 a.m.