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Depot One Comp PK ignoring BLQ observations.

[Generated automatically as a Fitting summary]

Inputs

Description

Name:blq_pk_norm_fit_ignore
Title:Depot One Comp PK ignoring BLQ observations.
Author:J.R. Hartley
Abstract:
Depot One Comp PK model, with BLQ (below level of quantification)
observations removed from data set.
Keywords:tutorial; pk; advan4; dep_two_cmp; blq
Input Script:blq_pk_norm_fit_ignore.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

-829.6140

which required 1.30 iterations and took 188.86 seconds

Final fitted fixed effects

f[KA] = 0.2246
f[CL] = 1.8588
f[V1] = 52.6500
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.0000, -0.0002, 0.0008 ],
    [ -0.0002, 0.0203, -0.0066 ],
    [ 0.0008, -0.0066, 0.1603 ],
]
f[PNOISE] = 0.1454
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 0.2246 0.7754 0.7754
f[CL] 1.0000 1.8588 0.8588 0.8588
f[V1] 20.0000 52.6500 1.6325 32.6500

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE] 0.1000 0.1454 0.4536 0.0454

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[KA_isv] 0.0500 0.0000 0.9998 0.0500
f[KA_isv;CL_isv] 0.0100 -0.0002 1.0201 0.0102
f[KA_isv;V1_isv] 0.0100 0.0008 0.9205 0.0092
f[CL_isv;KA_isv] 0.0100 -0.0002 1.0201 0.0102
f[CL_isv] 0.0500 0.0203 0.5946 0.0297
f[CL_isv;V1_isv] 0.0100 -0.0066 1.6605 0.0166
f[V1_isv;KA_isv] 0.0100 0.0008 0.9205 0.0092
f[V1_isv;CL_isv] 0.0100 -0.0066 1.6605 0.0166
f[V1_isv] 0.0500 0.1603 2.2059 0.1103
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