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Depot One Comp PK with BLQ observations set to LLQ

[Generated automatically as a Fitting summary]

Inputs

Description

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

122017.4388

which required N. iterations and took 117.20 seconds

Final fitted fixed effects

f[KA] = 1.2963
f[CL] = 0.9544
f[V1] = 88.6066
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.1648, -0.0018, -0.0048 ],
    [ -0.0018, 0.0021, -0.0113 ],
    [ -0.0048, -0.0113, 0.0643 ],
]
f[PNOISE] = 0.2379
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] 1.2963 1.0000 0.2963 0.2963
f[CL] 0.9544 1.0000 0.0456 0.0456
f[V1] 88.6066 20.0000 3.4303 68.6066

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE] 0.2379 0.1000 1.3786 0.1379

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[KA_isv] 0.1648 0.0500 2.2958 0.1148
f[KA_isv;CL_isv] -0.0018 0.0100 1.1806 0.0118
f[KA_isv;V1_isv] -0.0048 0.0100 1.4793 0.0148
f[CL_isv;KA_isv] -0.0018 0.0100 1.1806 0.0118
f[CL_isv] 0.0021 0.0500 0.9576 0.0479
f[CL_isv;V1_isv] -0.0113 0.0100 2.1305 0.0213
f[V1_isv;KA_isv] -0.0048 0.0100 1.4793 0.0148
f[V1_isv;CL_isv] -0.0113 0.0100 2.1305 0.0213
f[V1_isv] 0.0643 0.0500 0.2856 0.0143
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