- Language: en
- Documentation version: 1.3.1
Depot + One compartment PK with BLQ
[Generated automatically as a Tutorial summary]
Model Description
- Name:
blq_pk
- Title:
Depot + One compartment PK with BLQ
- Author:
PoPy for PK/PD
- Abstract:
- Keywords:
tutorial; pk; advan4; dep_two_cmp; blq
- Input Script:
- Diagram:
Comparison
True objective value
-763.2175
Final fitted objective value
-767.6650
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA] |
1 |
0.199 |
0.2 |
9.47e-04 |
0.47% |
f[CL] |
1 |
1.95 |
2 |
5.25e-02 |
2.62% |
f[V1] |
20 |
48.7 |
50 |
1.28e+00 |
2.56% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[PNOISE] |
0.1 |
0.149 |
0.15 |
1.12e-03 |
0.75% |
Compare Variance f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA_isv] |
0.05 |
0.0681 |
0.1 |
3.19e-02 |
31.93% |
f[KA_isv;CL_isv] |
0.01 |
0.033 |
0.02 |
1.30e-02 |
64.95% |
f[KA_isv;V1_isv] |
0.01 |
-0.000844 |
0.01 |
1.08e-02 |
108.44% |
f[CL_isv;KA_isv] |
0.01 |
0.033 |
0.02 |
1.30e-02 |
64.95% |
f[CL_isv] |
0.05 |
0.0385 |
0.03 |
8.55e-03 |
28.49% |
f[CL_isv;V1_isv] |
0.01 |
0.031 |
0.02 |
1.10e-02 |
55.14% |
f[V1_isv;KA_isv] |
0.01 |
-0.000844 |
0.01 |
1.08e-02 |
108.44% |
f[V1_isv;CL_isv] |
0.01 |
0.031 |
0.02 |
1.10e-02 |
55.14% |
f[V1_isv] |
0.05 |
0.103 |
0.09 |
1.29e-02 |
14.34% |
Outputs
Fitted f[X] values (after fitting)
f[KA] = 0.1991
f[CL] = 1.9475
f[V1] = 48.7184
f[KA_isv,CL_isv,V1_isv] = [
[ 0.0681, 0.0330, -0.0008 ],
[ 0.0330, 0.0385, 0.0310 ],
[ -0.0008, 0.0310, 0.1029 ],
]
f[PNOISE] = 0.1489
f[ANOISE] = 0.0100
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: Depot + One compartment PK with BLQ (gen)
Fit: Depot + One compartment PK with BLQ (fit)
Inputs
True f[X] values (for simulation)
f[KA] = 0.2000
f[CL] = 2.0000
f[V1] = 50.0000
f[KA_isv,CL_isv,V1_isv] = [
[ 0.1000, 0.0200, 0.0100 ],
[ 0.0200, 0.0300, 0.0200 ],
[ 0.0100, 0.0200, 0.0900 ],
]
f[PNOISE] = 0.1500
f[ANOISE] = 0.0100
Starting f[X] values (before fitting)
f[KA] = 1.0000
f[CL] = 1.0000
f[V1] = 20.0000
f[KA_isv,CL_isv,V1_isv] = [
[ 0.0500, 0.0100, 0.0100 ],
[ 0.0100, 0.0500, 0.0100 ],
[ 0.0100, 0.0100, 0.0500 ],
]
f[PNOISE] = 0.1000
f[ANOISE] = 0.0100