- Language: en
Mixed error model fitted to mixed error data, but with incorrect variance definition¶
[Generated automatically as a Fitting summary]
Model Description¶
| Name: | pa_gen_pa_fit_badvar |
|---|---|
| Title: | Mixed error model fitted to mixed error data, but with incorrect variance definition |
| 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, but erroneously sums the standard deviations.
| Keywords: | one compartment model; dep_one_cmp_cl; proportional and additive error |
|---|---|
| Input Script: | pa_gen_pa_fit_badvar.pyml |
| 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 | 0.0699 | 0.4301 | 0.8603 |
| f[ANOISE_STD] | 0.2500 | 0.0400 | 0.2100 | 0.8399 |
Compare Variance f[X]¶
Population observed (fit) plots¶
|
indOBS_vs_TIME |
Population simulated (sim) plots¶
|
indOBS_vs_TIME |
Outputs¶
Fitted f[X] values (after fitting)¶
f[PNOISE_STD] = 0.0699
f[ANOISE_STD] = 0.0400
Fitted parameter .csv files¶
| Fixed Effects: | fx_params.csv (fit) |
|---|---|
| Random Effects: | rx_params.csv (fit) |
| Model params: | mx_params.csv (fit) |
| State values: | sx_params.csv (fit) |
| Predictions: | px_params.csv (fit) |
| Likelihoods: | lx_params.csv (fit) |
Inputs¶
| Input Data: | synthetic_data.csv |
|---|
Starting f[X] values (before fitting)¶
f[PNOISE_STD] = 0.5000
f[ANOISE_STD] = 0.2500