Flip Flop tutorial with low initial estimates of KA, V and CL

[Generated automatically as a Generation summary]

Model Description

Name:

flip_flop_good_pop

Title:

Flip Flop tutorial with low initial estimates of KA, V and CL

Author:

PoPy for PK/PD

Abstract:

One compartment model with a depot leading into a central compartment.
Note another interpretation of this is that the model is just over parametrised. Because here
the KE and V parameters act independently unlike the CL/V and V parametrisation.
Here initial values of KE, KA, V are close to the flipped values, so we get a good fit near the true global minima.
Keywords:

one compartment model; flip flop; dep_one_cmp_k; good start values

Input Script:

flip_flop_good_pop_gen.pyml

Diagram:

Outputs

Individual simulated (sim) plots

Alternatively see All simulated_sim graph plots

Population simulated (sim) plots

(No population graphs were requested.)

Generated parameter .csv files

Fixed Effects:

fx_params.csv (gen)

Random Effects:

rx_params.csv (gen)

Model params:

mx_params.csv (gen)

State values:

sx_params.csv (gen)

Predictions:

px_params.csv (gen)

Observations:

synthetic_data.csv (gen)

Inputs

True f[X] values (for simulation)

f[KE] = 0.0500
f[V] = 40.0000
f[KA] = 0.6000
f[PNOISE] = 0.0100
f[ANOISE] = 0.0500
f[KE_isv,V_isv,KA_isv] = [
    [ 0.0500, 0.0000, 0.0000 ],
    [ 0.0000, 0.0500, 0.0000 ],
    [ 0.0000, 0.0000, 0.0500 ],
]