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

[Generated automatically as a Tutorial 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_tut.pyml
Diagram:

Comparison

True objective value

-275.3301

Final fitted objective value

-282.2497

Compare Main f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KE]	0.02	0.0494	0.05	6.16e-04	1.23%
f[V]	30	39.5	40	5.07e-01	1.27%
f[KA]	0.3	0.572	0.6	2.84e-02	4.73%

Compare Noise f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[PNOISE]	0.05	0.00693	0.01	3.07e-03	30.71%
f[ANOISE]	0.1	0.0536	0.05	3.56e-03	7.12%

Compare Variance f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KE_isv]	0.02	0.0439	0.05	6.07e-03	12.13%
f[KE_isv;V_isv]	0	-0.00841	0	8.41e-03	inf
f[KE_isv;KA_isv]	0	0.00913	0	9.13e-03	inf
f[V_isv;KE_isv]	0	-0.00841	0	8.41e-03	inf
f[V_isv]	0.02	0.0374	0.05	1.26e-02	25.18%
f[V_isv;KA_isv]	0	0.0168	0	1.68e-02	inf
f[KA_isv;KE_isv]	0	0.00913	0	9.13e-03	inf
f[KA_isv;V_isv]	0	0.0168	0	1.68e-02	inf
f[KA_isv]	0.02	0.0439	0.05	6.11e-03	12.23%

Outputs

Fitted f[X] values (after fitting)

f[KE] = 0.0494
f[V] = 39.4926
f[KA] = 0.5716
f[PNOISE] = 0.0069
f[ANOISE] = 0.0536
f[KE_isv,V_isv,KA_isv] = [
    [ 0.0439, -0.0084, 0.0091 ],
    [ -0.0084, 0.0374, 0.0168 ],
    [ 0.0091, 0.0168, 0.0439 ],
]

Generated data .csv file

Synthetic Data:: synthetic_data.csv

Gen and Fit Summaries

Gen: Flip Flop tutorial with low initial estimates of KA, V and CL (gen)
Fit: Flip Flop tutorial with low initial estimates of KA, V and CL (fit)

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 ],
]

Starting f[X] values (before fitting)

f[KE] = 0.0200
f[V] = 30.0000
f[KA] = 0.3000
f[PNOISE] = 0.0500
f[ANOISE] = 0.1000
f[KE_isv,V_isv,KA_isv] = [
    [ 0.0200, 0.0000, 0.0000 ],
    [ 0.0000, 0.0200, 0.0000 ],
    [ 0.0000, 0.0000, 0.0200 ],
]