Depot One Comp PK with BLQ observations set to 0.5*LLQ

[Generated automatically as a Fitting summary]

Model Description

Name:: blq_pk_norm_fit_half
Title:: Depot One Comp PK with BLQ observations set to 0.5*LLQ
Author:: PoPy for PK/PD
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
Diagram:

Comparison

Compare Main f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[KA]	1.0000	1.1546	0.1546	0.1546
f[CL]	1.0000	1.6274	0.6274	0.6274
f[V1]	20.0000	77.9502	57.9502	2.8975

Compare Noise f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[PNOISE]	0.1000	0.3270	0.2270	2.2698

Compare Variance f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[KA_isv]	0.0500	0.3676	0.3176	6.3524
f[KA_isv;CL_isv]	0.0100	0.0643	0.0543	5.4283
f[KA_isv;V1_isv]	0.0100	0.1502	0.1402	14.0225
f[CL_isv;KA_isv]	0.0100	0.0643	0.0543	5.4283
f[CL_isv]	0.0500	0.0115	0.0385	0.7700
f[CL_isv;V1_isv]	0.0100	0.0269	0.0169	1.6855
f[V1_isv;KA_isv]	0.0100	0.1502	0.1402	14.0225
f[V1_isv;CL_isv]	0.0100	0.0269	0.0169	1.6855
f[V1_isv]	0.0500	0.0628	0.0128	0.2553

Individual simulated (sim) plots

Alternatively see All simulated_sim graph plots

Population simulated (sim) plots

(No population graphs were requested.)

Outputs

Final objective value

28176.6771

which required 1.30 iterations and took 67.67 seconds

Fitted f[X] values (after fitting)

f[KA] = 1.1546
f[CL] = 1.6274
f[V1] = 77.9502
f[KA_isv,CL_isv,V1_isv] = [
    [ 0.3676, 0.0643, 0.1502 ],
    [ 0.0643, 0.0115, 0.0269 ],
    [ 0.1502, 0.0269, 0.0628 ],
]
f[PNOISE] = 0.3270
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