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Full matrix generation full matrix fit

[Generated automatically as a Fitting summary]

Inputs

Description

Name:gen_full_fit_full
Title:Full matrix generation full matrix fit
Author:Wright Dose Ltd
Abstract:
One compartment model with absorption compartment and CL/V parametrisation.
This script uses a full covariance matrix to generate the data and a full covariance matrix to fit.
Keywords:dep_one_cmp_cl; one compartment model; full matrix
Input Script:gen_full_fit_full_fit.pyml
Input Data:synthetic_data.csv
Diagram:

Initial fixed effect estimates

f[KA] = 0.3000
f[CL] = 3.0000
f[V] = 20.0000
f[PNOISE_STD] = 0.1000
f[ANOISE_STD] = 0.0500
f[CL_isv,V_isv] = [
    [ 0.0100, 0.0010 ],
    [ 0.0010, 0.0100 ],
]

Outputs

Final objective value

-2108.2792

which required 1.11 iterations and took 1008.95 seconds

Final fitted fixed effects

f[KA] = 0.3000
f[CL] = 3.0000
f[V] = 20.0000
f[PNOISE_STD] = 0.1000
f[ANOISE_STD] = 0.0500
f[CL_isv,V_isv] = [
    [ 0.1361, 0.0500 ],
    [ 0.0500, 0.1660 ],
]

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]

Compare Noise f[X]

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[CL_isv] 0.0100 0.1361 12.6072 0.1261
f[CL_isv;V_isv] 0.0010 0.0500 48.9950 0.0490
f[V_isv;CL_isv] 0.0010 0.0500 48.9950 0.0490
f[V_isv] 0.0100 0.1660 15.5991 0.1560
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