Depot One Comp PK with BLQ observations set to LLQ

[Generated automatically as a Fitting summary]

Model Description

Name:: blq_pk_norm_fit
Title:: Depot One Comp PK with BLQ observations set to LLQ
Author:: PoPy for PK/PD
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
Diagram:

Comparison

Compare Main f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[KA]	1.0000	4.6504	3.6504	3.6504
f[CL]	1.0000	0.9495	0.0505	0.0505
f[V1]	20.0000	85.1296	65.1296	3.2565

Compare Noise f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[PNOISE]	0.1000	0.2299	0.1299	1.2986

Compare Variance f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[KA_isv]	0.0500	1.3306	1.2806	25.6112
f[KA_isv;CL_isv]	0.0100	-0.0040	0.0140	1.4012
f[KA_isv;V1_isv]	0.0100	0.2688	0.2588	25.8834
f[CL_isv;KA_isv]	0.0100	-0.0040	0.0140	1.4012
f[CL_isv]	0.0500	0.0000	0.0500	0.9997
f[CL_isv;V1_isv]	0.0100	-0.0008	0.0108	1.0788
f[V1_isv;KA_isv]	0.0100	0.2688	0.2588	25.8834
f[V1_isv;CL_isv]	0.0100	-0.0008	0.0108	1.0788
f[V1_isv]	0.0500	0.0586	0.0086	0.1720

Individual simulated (sim) plots

Alternatively see All simulated_sim graph plots

Population simulated (sim) plots

(No population graphs were requested.)

Outputs

Final objective value

122012.4198

which required 1.30 iterations and took 74.73 seconds

Fitted f[X] values (after fitting)

f[KA] = 4.6504
f[CL] = 0.9495
f[V1] = 85.1296
f[KA_isv,CL_isv,V1_isv] = [
    [ 1.3306, -0.0040, 0.2688 ],
    [ -0.0040, 0.0000, -0.0008 ],
    [ 0.2688, -0.0008, 0.0586 ],
]
f[PNOISE] = 0.2299
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)
Likelihoods:: lx_params.csv (fit)

Inputs

Input Data:: synthetic_data.csv

Starting f[X] values (before fitting)

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