calculate_pk_parameters_statistics#

pharmpy.modeling.calculate_pk_parameters_statistics(model, parameter_estimates, covariance_matrix=None, seed=None)[source]#

Calculate statistics for common pharmacokinetic parameters

Calculate the mean (expected value of the distribution), variance (variance of the distribution) and standard error for some individual pre-defined pharmacokinetic parameters.

Parameters:

model (Model) – A previously estimated model
parameter_estimates (pd.Series) – Parameter estimates
covariance_matrix (pd.DataFrame) – Parameter uncertainty covariance matrix
seed (Generator or int) – Random number generator or seed

Returns:

pd.DataFrame – A DataFrame of statistics indexed on parameter and covariate value.

Examples

>>> from pharmpy.modeling import load_example_model, create_rng
>>> from pharmpy.modeling import calculate_pk_parameters_statistics
>>> from pharmpy.tools import load_example_modelfit_results
>>> model = load_example_model("pheno")
>>> results = load_example_modelfit_results("pheno")
>>> rng = create_rng(23)
>>> pe = results.parameter_estimates
>>> cov = results.covariance_matrix
>>> calculate_pk_parameters_statistics(model, pe, cov, seed=rng)
                              mean     variance     stderr
parameter   covariates
t_half_elim p5          173.337164  1769.493756  44.852625
            median      149.567842  1317.474199  37.819338
            p95         149.567842  1317.474199  37.819338
k_e         p5            0.004234     0.000001   0.001100
            median        0.004907     0.000001   0.001201
            p95           0.004907     0.000001   0.001201