set_proportional_error_model function

set_proportional_error_model

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) +------------------------+----------------------------------------+

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

Arguments

• model: (Model) Set error model for this model
• dv: (str or Expr 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

Returns

(Model) Pharmpy model object

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)

See Also

set_additive_error_model : Additive error model

set_combined_error_model : Combined error model