Model containing both proportional and additive error
[Generated automatically as a Fitting summary]
Model Description
- Name:
pa_gen_pa_fit
- Title:
Model containing both proportional and additive error
- Author:
PoPy for PK/PD
- Abstract:
One compartment model with a depot leading to a central compartment.
This model contains both proportional and additive error.
- Keywords:
one compartment model; one_two_cmp_cl; proportional and additive error
- Input Script:
- Diagram:
Failed to create compartment diagram
Comparison
Compare Main f[X]
Compare Noise f[X]
Variable Name |
Starting Value |
Fitted Value |
Abs Change |
Prop Change |
|---|---|---|---|---|
f[PNOISE_STD] |
0.5000 |
0.0951 |
0.4049 |
0.8098 |
f[ANOISE_STD] |
0.2500 |
0.0453 |
0.2047 |
0.8187 |
Compare Variance f[X]
Population simulated (sim) plots
|
allOBS_vs_TIME |
|
CWRES(DV_CENTRAL)_vs_IPRED(DV_CENTRAL) |
|
indOBS_vs_TIME |
|
IRES(DV_CENTRAL)_vs_IPRED(DV_CENTRAL) |
|
WRES(DV_CENTRAL)_vs_PPRED(DV_CENTRAL) |
Outputs
Final objective value
-396.6598
which required 1.6 iterations and took 0.73 seconds
Fitted f[X] values (after fitting)
f[PNOISE_STD] = 0.0951
f[ANOISE_STD] = 0.0453
Fitted parameter .csv files
- Fixed Effects:
- Random Effects:
- Model params:
- State values:
- Predictions:
- Likelihoods:
Inputs
- Input Data:
Starting f[X] values (before fitting)
f[PNOISE_STD] = 0.5000
f[ANOISE_STD] = 0.2500