• Language: en

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

28174.8044

which required N. iterations and took 389.29 seconds

Final fitted fixed effects

f[KA] = 1.3657
f[CL] = 1.6485
f[V1] = 78.8853
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.1806, 0.0094, 0.0283 ],
    [ 0.0094, 0.0123, 0.0281 ],
    [ 0.0283, 0.0281, 0.0647 ],
]
f[PNOISE] = 0.3372
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] 1.3657 1.0000 0.3657 0.3657
f[CL] 1.6485 1.0000 0.6485 0.6485
f[V1] 78.8853 20.0000 2.9443 58.8853

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE] 0.3372 0.1000 2.3722 0.2372

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[KA_isv] 0.1806 0.0500 2.6125 0.1306
f[KA_isv;CL_isv] 0.0094 0.0100 0.0581 0.0006
f[KA_isv;V1_isv] 0.0283 0.0100 1.8318 0.0183
f[CL_isv;KA_isv] 0.0094 0.0100 0.0581 0.0006
f[CL_isv] 0.0123 0.0500 0.7542 0.0377
f[CL_isv;V1_isv] 0.0281 0.0100 1.8137 0.0181
f[V1_isv;KA_isv] 0.0283 0.0100 1.8318 0.0183
f[V1_isv;CL_isv] 0.0281 0.0100 1.8137 0.0181
f[V1_isv] 0.0647 0.0500 0.2941 0.0147
Back to Top