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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

122016.6973

which required N. iterations and took 91.02 seconds

Final fitted fixed effects

f[KA] = 1.2697
f[CL] = 0.9437
f[V1] = 89.5814
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.1630, -0.0014, -0.0034 ],
    [ -0.0014, 0.0021, -0.0112 ],
    [ -0.0034, -0.0112, 0.0666 ],
]
f[PNOISE] = 0.2321
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 Fitted Value Starting Value Prop Change Abs Change
f[KA] 1.2697 1.0000 0.2697 0.2697
f[CL] 0.9437 1.0000 0.0563 0.0563
f[V1] 89.5814 20.0000 3.4791 69.5814

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE] 0.2321 0.1000 1.3205 0.1321

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[KA_isv] 0.1630 0.0500 2.2609 0.1130
f[KA_isv;CL_isv] -0.0014 0.0100 1.1411 0.0114
f[KA_isv;V1_isv] -0.0034 0.0100 1.3385 0.0134
f[CL_isv;KA_isv] -0.0014 0.0100 1.1411 0.0114
f[CL_isv] 0.0021 0.0500 0.9582 0.0479
f[CL_isv;V1_isv] -0.0112 0.0100 2.1168 0.0212
f[V1_isv;KA_isv] -0.0034 0.0100 1.3385 0.0134
f[V1_isv;CL_isv] -0.0112 0.0100 2.1168 0.0212
f[V1_isv] 0.0666 0.0500 0.3318 0.0166
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