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Depot One Comp PK with BLQ observations set to 0.5*LLQ

[Generated automatically as a Fitting summary]

Inputs

Description

Name:blq_pk_norm_fit_half
Title:Depot One Comp PK with BLQ observations set to 0.5*LLQ
Author:J.R. Hartley
Abstract:
Depot One Comp PK model, with BLQ (below level of quantification)
observations set to 0.5*LLQ (lower limit of quantification).
Keywords:tutorial; pk; advan4; dep_two_cmp; blq
Input Script:blq_pk_norm_fit_half.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

28168.9208

which required 1.30 iterations and took 305.57 seconds

Final fitted fixed effects

f[KA] = 0.6179
f[CL] = 1.6995
f[V1] = 83.1400
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.0000, 0.0007, 0.0017 ],
    [ 0.0007, 0.0110, 0.0270 ],
    [ 0.0017, 0.0270, 0.0663 ],
]
f[PNOISE] = 0.3362
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 0.6179 0.3821 0.3821
f[CL] 1.0000 1.6995 0.6995 0.6995
f[V1] 20.0000 83.1400 3.1570 63.1400

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE] 0.1000 0.3362 2.3615 0.2362

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[KA_isv] 0.0500 0.0000 0.9991 0.0500
f[KA_isv;CL_isv] 0.0100 0.0007 0.9314 0.0093
f[KA_isv;V1_isv] 0.0100 0.0017 0.8315 0.0083
f[CL_isv;KA_isv] 0.0100 0.0007 0.9314 0.0093
f[CL_isv] 0.0500 0.0110 0.7802 0.0390
f[CL_isv;V1_isv] 0.0100 0.0270 1.6987 0.0170
f[V1_isv;KA_isv] 0.0100 0.0017 0.8315 0.0083
f[V1_isv;CL_isv] 0.0100 0.0270 1.6987 0.0170
f[V1_isv] 0.0500 0.0663 0.3259 0.0163
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