set_proportional_error_model: set_proportional_error_model

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

set_proportional_error_model

Description

Set a proportional error model. Initial estimate for new sigma is 0.09.

The error function being applied depends on the data transformation.

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

Usage

set_proportional_error_model(
  model,
  dv = NULL,
  data_trans = NULL,
  zero_protection = TRUE
)

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.
zero_protection	(logical) Set to TRUE to add code protecting from IPRED=0

Value

(Model) Pharmpy model object

See Also

set_additive_error_model : Additive error model

set_combined_error_model : Combined error model

Examples

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

## End(Not run)

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