- Language: en
Simple Tut Example¶
[Generated automatically as a Fitting summary]
Inputs¶
Description¶
| Name: | tut_example1 |
|---|---|
| Title: | Simple Tut Example |
| Author: | J.R. Hartley |
| Abstract: |
One compartment model with elimination rate constant KE.
| Keywords: | one compartment model; iv_one_cmp_k |
|---|---|
| Input Script: | tut_example1_fit.pyml |
| Input Data: | synthetic_data.csv |
| Diagram: |
Initial fixed effect estimates¶
f[KE] = 0.0500
f[PNOISE] = 0.1000
f[KE_isv] = 0.1000
Outputs¶
Final fitted fixed effects¶
f[KE] = 0.1062
f[PNOISE] = 0.0449
f[KE_isv] = 0.0274
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) |
Plots¶
Comparison¶
Compare Main f[X]¶
| Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[KE] | 0.1062 | 0.0500 | 1.1234 | 0.0562 |
Compare Noise f[X]¶
| Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[PNOISE] | 0.0449 | 0.1000 | 0.5506 | 0.0551 |
Compare Variance f[X]¶
| Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[KE_isv] | 0.0274 | 0.1000 | 0.7261 | 0.0726 |