Depot One Comp PK with BLQ observations set to LLQ¶
[Generated automatically as a Fitting summary]
Inputs¶
Description¶
| Name: | blq_pk_norm_fit |
|---|---|
| Title: | Depot One Comp PK with BLQ observations set to LLQ |
| Author: | J.R. Hartley |
| Abstract: |
Depot One Comp PK model, with BLQ (below level of quantification)
observations set to LLQ (lower limit of quantification).
| Keywords: | tutorial; pk; advan4; dep_two_cmp; blq |
|---|---|
| Input Script: | blq_pk_norm_fit.pyml |
| Input Data: | synthetic_data.csv |
| Diagram: |
Initial fixed effect estimates¶
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
Outputs¶
Final fitted fixed effects¶
f[KA] = 2.8234
f[CL] = 0.9554
f[V1] = 86.0572
f[KA_isv,CL_isv,V1_isv] = [
[ 1.2020, -0.0141, 0.2416 ],
[ -0.0141, 0.0002, -0.0029 ],
[ 0.2416, -0.0029, 0.0501 ],
]
f[PNOISE] = 0.2289
f[ANOISE] = 0.0100
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 | Starting Value | Fitted Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[KA] | 1.0000 | 2.8234 | 1.8234 | 1.8234 |
| f[CL] | 1.0000 | 0.9554 | 0.0446 | 0.0446 |
| f[V1] | 20.0000 | 86.0572 | 3.3029 | 66.0572 |
Compare Noise f[X]¶
| Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[PNOISE] | 0.1000 | 0.2289 | 1.2885 | 0.1289 |
Compare Variance f[X]¶
| Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[KA_isv] | 0.0500 | 1.2020 | 23.0400 | 1.1520 |
| f[KA_isv;CL_isv] | 0.0100 | -0.0141 | 2.4087 | 0.0241 |
| f[KA_isv;V1_isv] | 0.0100 | 0.2416 | 23.1607 | 0.2316 |
| f[CL_isv;KA_isv] | 0.0100 | -0.0141 | 2.4087 | 0.0241 |
| f[CL_isv] | 0.0500 | 0.0002 | 0.9966 | 0.0498 |
| f[CL_isv;V1_isv] | 0.0100 | -0.0029 | 1.2859 | 0.0129 |
| f[V1_isv;KA_isv] | 0.0100 | 0.2416 | 23.1607 | 0.2316 |
| f[V1_isv;CL_isv] | 0.0100 | -0.0029 | 1.2859 | 0.0129 |
| f[V1_isv] | 0.0500 | 0.0501 | 0.0027 | 0.0001 |