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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 objective value

121987.0135

which required 1.30 iterations and took 545.76 seconds

Final fitted fixed effects

f[KA] = 2.6741
f[CL] = 0.9560
f[V1] = 86.0580
f[KA_isv,CL_isv,V1_isv] = [
    [ 1.1328, -0.0132, 0.2360 ],
    [ -0.0132, 0.0002, -0.0028 ],
    [ 0.2360, -0.0028, 0.0504 ],
]
f[PNOISE] = 0.2288
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

Dense sim plots

Alternatively see All dense_sim graph plots

Comparison

Compare Main f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[KA] 1.0000 2.6741 1.6741 1.6741
f[CL] 1.0000 0.9560 0.0440 0.0440
f[V1] 20.0000 86.0580 3.3029 66.0580

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE] 0.1000 0.2288 1.2885 0.1288

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[KA_isv] 0.0500 1.1328 21.6551 1.0828
f[KA_isv;CL_isv] 0.0100 -0.0132 2.3154 0.0232
f[KA_isv;V1_isv] 0.0100 0.2360 22.5972 0.2260
f[CL_isv;KA_isv] 0.0100 -0.0132 2.3154 0.0232
f[CL_isv] 0.0500 0.0002 0.9968 0.0498
f[CL_isv;V1_isv] 0.0100 -0.0028 1.2760 0.0128
f[V1_isv;KA_isv] 0.0100 0.2360 22.5972 0.2260
f[V1_isv;CL_isv] 0.0100 -0.0028 1.2760 0.0128
f[V1_isv] 0.0500 0.0504 0.0087 0.0004
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