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Model containing proportional error only, with proportional only data

[Generated automatically as a Fitting summary]

Model Description

Name:

po_gen_po_fit

Title:

Model containing proportional error only, with proportional only data

Author:

PoPy for PK/PD

Abstract:

One compartment model with a depot leading to a central compartment.
This model contains proportional error and no additive error. The synthetic input data contains only proportional error too.
Keywords:

one compartment model; dep_one_cmp_cl; proportional error

Input Script:

po_gen_po_fit_fit.pyml

Diagram:

Failed to create compartment diagram

Comparison

Compare Main f[X]

Compare Noise f[X]

Variable Name

Starting Value

Fitted Value

Abs Change

Prop Change

f[PNOISE_STD]

0.5000

0.0932

0.4068

0.8136

Compare Variance f[X]

Population simulated (sim) plots

allOBS_vs_TIME

CWRES(DV_CENTRAL)_vs_IPRED(DV_CENTRAL)

indOBS_vs_TIME

IRES(DV_CENTRAL)_vs_IPRED(DV_CENTRAL)

WRES(DV_CENTRAL)_vs_PPRED(DV_CENTRAL)

Outputs

Final objective value

-572.8210

which required 1.7 iterations and took 0.84 seconds

Fitted f[X] values (after fitting)

f[PNOISE_STD] = 0.0932

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:

cx_obs_params.csv

Starting f[X] values (before fitting)

f[PNOISE_STD] = 0.5000
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