predict.pk {invivoPKfit} | R Documentation |
Get predictions
Description
Extract predictions from a fitted 'pk' object.
Usage
## S3 method for class 'pk'
predict(
object,
newdata = NULL,
model = NULL,
method = NULL,
type = "conc",
exclude = TRUE,
use_scale_conc = FALSE,
suppress.messages = NULL,
include_NAs = FALSE,
...
)
Arguments
object |
A [pk] object. |
newdata |
Optional: A 'data.frame' with new data for which to make predictions. If NULL (the default), then predictions will be made for the data in 'object$data'. 'newdata' is required to contain at least the following variables: 'Time', 'Time.Units', 'Dose', 'Route', and 'Media'. |
model |
Optional: Specify one or more of the fitted models for which to make predictions. If NULL (the default), predictions will be returned for all of the models in 'object$stat_model'. |
method |
Optional: Specify one or more of the [optimx::optimx()] methods for which to make predictions. If NULL (the default), predictions will be returned for all of the models in 'object$settings_optimx$method'. |
type |
Either '"conc"' (the default) or '"auc"'. 'type = "conc"' predicts concentrations; 'type = "auc"' predicts area under the concentration-time curve (AUC). |
exclude |
Logical: 'TRUE' to return 'NA_real_' for any observations in the data marked for exclusion (if there is a variable 'exclude' in the data, an observation is marked for exclusion when 'exclude 'FALSE' to return the prediction for each observation, regardless of exclusion. Default 'TRUE'. |
use_scale_conc |
Possible values: 'TRUE', 'FALSE', or a named list with elements 'dose_norm' and 'log10_trans' which themselves should be either 'TRUE' or 'FALSE'. If 'use_scale_conc = TRUE', then the concentration scaling/transformations in 'object' will be applied to both predicted and observed concentrations before the log-likelihood is computed. If 'use_scale_conc = FALSE' (the default for this function), then no concentration scaling or transformation will be applied before the log-likelihood is computed. If 'use_scale_conc = list(dose_norm = ..., log10_trans = ...)', then the specified dose normalization and/or log10-transformation will be applied. |
suppress.messages |
Logical: whether to suppress message printing. If NULL (default), uses the setting in 'object$settings_preprocess$suppress.messages' |
include_NAs |
Logical: 'FALSE' by default. Determines whether to include aborted fits which have NAs as coefficients. |
... |
Additional arguments. |
Value
A data.frame with one row for each 'data_group', 'model' and 'method'. Includes variable 'Conc_est' that contains the predicted concentration or AUC at that timepoint given the TK parameters for that 'model' and 'method' specified in [coefs()]. If 'use_scale_conc un-transformed concentrations in the same units as 'object$data$Conc.Units'. If 'use_scale_conc concentrations in the same units as 'object$data$Conc_trans.Units'.
Author(s)
Caroline Ring, Gilberto Padilla Mercado
See Also
Other methods for fitted pk objects:
AAFE.pk()
,
AFE.pk()
,
AIC.pk()
,
BIC.pk()
,
coef.pk()
,
coef_sd.pk()
,
eval_tkstats.pk()
,
get_fit.pk()
,
get_hessian.pk()
,
get_tkstats.pk()
,
logLik.pk()
,
residuals.pk()
,
rmse.pk()
,
rsq.pk()