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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

-834.2742

which required N. iterations and took 240.84 seconds

Final fitted fixed effects

f[KA] = 0.2292
f[CL] = 1.8316
f[V1] = 53.1015
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.0175, 0.0115, 0.0270 ],
    [ 0.0115, 0.0142, -0.0103 ],
    [ 0.0270, -0.0103, 0.1778 ],
]
f[PNOISE] = 0.1437
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] 0.2292 1.0000 0.7708 0.7708
f[CL] 1.8316 1.0000 0.8316 0.8316
f[V1] 53.1015 20.0000 1.6551 33.1015

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE] 0.1437 0.1000 0.4367 0.0437

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[KA_isv] 0.0175 0.0500 0.6491 0.0325
f[KA_isv;CL_isv] 0.0115 0.0100 0.1534 0.0015
f[KA_isv;V1_isv] 0.0270 0.0100 1.7038 0.0170
f[CL_isv;KA_isv] 0.0115 0.0100 0.1534 0.0015
f[CL_isv] 0.0142 0.0500 0.7164 0.0358
f[CL_isv;V1_isv] -0.0103 0.0100 2.0296 0.0203
f[V1_isv;KA_isv] 0.0270 0.0100 1.7038 0.0170
f[V1_isv;CL_isv] -0.0103 0.0100 2.0296 0.0203
f[V1_isv] 0.1778 0.0500 2.5558 0.1278
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