get_winning_model.pk {invivoPKfit} | R Documentation |
Get winning model
Description
Get winning model for a fitted 'pk' object
Usage
## S3 method for class 'pk'
get_winning_model(obj, newdata = NULL, method = NULL, criterion = "AIC", ...)
Arguments
obj |
A [pk()] object |
newdata |
Optional: A 'data.frame' containing new data to plot. Must contain at least variables 'Chemical', 'Species', 'Route', 'Media', 'Dose', 'Time', 'Time.Units', 'Conc', 'Detect', 'Conc_SD'. Default 'NULL', to use the data in 'obj$data'. |
method |
Character: One or more of the [optimx::optimx()] methods used in fitting. The winning model will be determined for each of these methods. Default 'NULL' to get the winning model for each method in 'obj$settings_optimx$method'. |
criterion |
The name of a criterion function to use for model comparison. Default "AIC". Must be the name of a function that (as for 'AIC') accepts arguments 'obj', 'newdata', 'method' and 'model' (may accept other arguments, specified in '...') and returns output as for 'AIC': a data.frame with a column with the same name as 'criterion' that has calculated values for model comparison. The "winning" value will be the smallest value. |
... |
Optional: Other arguments to 'criterion' function. |
Details
Get the winning model (i.e. the model with the lowest value of the criterion specified in 'criterion') for a fitted 'pk' object, for a specified method, and optionally for a specified new dataset. When there are ties it will return the first encounter, where the priority is: model_1comp > model_2comp > model_flat.
Value
A data.frame with one row for each 'data_group', 'model' and 'method' and The return value has attribute 'criterion' giving the name of the criterion function used to compare models.
Author(s)
Caroline Ring, Gilberto Padilla Mercado