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

[Generated automatically as a Tutorial summary]

Model Description

Name:

flip_flop_good

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.

Here initial values of KE, KA, V are close to the true values, so we get a good fit near the true global minima.

Keywords:

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

Input Script:

flip_flop_good_tut.pyml

Diagram:

Comparison

True objective value

86.0288

Final fitted objective value

83.4768

Compare Main f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KA]	0.5	0.153	0.15	2.57e-03	1.72%
f[KE]	0.5	0.301	0.3	1.41e-03	0.47%

Compare Noise f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[ANOISE_STD]	5	0.921	1	7.93e-02	7.93%

Compare Variance f[X]

No Variance f[X] values to compare.

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.1526
f[KE] = 0.3014
f[ANOISE_STD] = 0.9207

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[KA] = 0.1500
f[KE] = 0.3000
f[ANOISE_STD] = 1.0000

Starting f[X] values (before fitting)

f[KA] = 0.5000
f[KE] = 0.5000
f[ANOISE_STD] = 5.0000