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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

28169.3064

which required 1.30 iterations and took 368.46 seconds

Final fitted fixed effects

f[KA] = 1.3656
f[CL] = 1.6576
f[V1] = 80.4195
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.7858, 0.0888, 0.2165 ],
    [ 0.0888, 0.0103, 0.0250 ],
    [ 0.2165, 0.0250, 0.0610 ],
]
f[PNOISE] = 0.3307
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 1.3656 0.3656 0.3656
f[CL] 1.0000 1.6576 0.6576 0.6576
f[V1] 20.0000 80.4195 3.0210 60.4195

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE] 0.1000 0.3307 2.3067 0.2307

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[KA_isv] 0.0500 0.7858 14.7152 0.7358
f[KA_isv;CL_isv] 0.0100 0.0888 7.8834 0.0788
f[KA_isv;V1_isv] 0.0100 0.2165 20.6473 0.2065
f[CL_isv;KA_isv] 0.0100 0.0888 7.8834 0.0788
f[CL_isv] 0.0500 0.0103 0.7945 0.0397
f[CL_isv;V1_isv] 0.0100 0.0250 1.4994 0.0150
f[V1_isv;KA_isv] 0.0100 0.2165 20.6473 0.2065
f[V1_isv;CL_isv] 0.0100 0.0250 1.4994 0.0150
f[V1_isv] 0.0500 0.0610 0.2195 0.0110
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