set_additive_error_model function

set_additive_error_model

Set an additive error model. Initial estimate for new sigma is (equation could not be rendered, see API doc on website)

The error function being applied depends on the data transformation. The table displays some examples.

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

set_additive_error_model(model, dv = NULL, data_trans = NULL, series_terms = 2)

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. Series expansion will be used for approximation.
• series_terms: (numeric) Number of terms to use for the series expansion approximation for data transformation.

Returns

(Model) Pharmpy model object

Examples

## Not run:

model <- load_example_model("pheno")
model$statements$find_assignment("Y")
model <- set_additive_error_model(model)
model$statements$find_assignment("Y")
model <- load_example_model("pheno")
model$statements$find_assignment("Y")
model <- set_additive_error_model(model, data_trans="log(Y)")
model$statements$find_assignment("Y")
## End(Not run)

See Also

set_proportional_error_model : Proportional error model

set_combined_error_model : Combined error model