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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

28174.9807

which required N. iterations and took 161.66 seconds

Final fitted fixed effects

f[KA] = 1.3315
f[CL] = 1.6939
f[V1] = 83.1212
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.2154, 0.0120, 0.0317 ],
    [ 0.0120, 0.0123, 0.0280 ],
    [ 0.0317, 0.0280, 0.0641 ],
]
f[PNOISE] = 0.3422
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] 1.3315 1.0000 0.3315 0.3315
f[CL] 1.6939 1.0000 0.6939 0.6939
f[V1] 83.1212 20.0000 3.1561 63.1212

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE] 0.3422 0.1000 2.4217 0.2422

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[KA_isv] 0.2154 0.0500 3.3084 0.1654
f[KA_isv;CL_isv] 0.0120 0.0100 0.2020 0.0020
f[KA_isv;V1_isv] 0.0317 0.0100 2.1664 0.0217
f[CL_isv;KA_isv] 0.0120 0.0100 0.2020 0.0020
f[CL_isv] 0.0123 0.0500 0.7531 0.0377
f[CL_isv;V1_isv] 0.0280 0.0100 1.8044 0.0180
f[V1_isv;KA_isv] 0.0317 0.0100 2.1664 0.0217
f[V1_isv;CL_isv] 0.0280 0.0100 1.8044 0.0180
f[V1_isv] 0.0641 0.0500 0.2821 0.0141
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