Proportional error model fitted to proportional + additive noise synthetic data.¶
[Generated automatically as a Fitting summary]
Inputs¶
Description¶
Name: | pa_gen_po_fit |
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Title: | Proportional error model fitted to proportional + additive noise synthetic data. |
Author: | Wright Dose Ltd |
Abstract: |
One compartment model with a depot leading to a central compartment
This model contains both proportional error only. Input data contains proportional and additive noise.
Keywords: | one compartment model; dep_one_cmp_cl; proportional error |
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Input Script: | pa_gen_po_fit.pyml |
Input Data: | synthetic_data.csv |
Diagram: |
Initial fixed effect estimates¶
f[PNOISE_STD] = 0.5000
Outputs¶
Final fitted fixed effects¶
f[PNOISE_STD] = 0.5223
Fitted parameter .csv files¶
Fixed Effects: | fx_params.csv (fit) |
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Random Effects: | rx_params.csv (fit) |
Model params: | mx_params.csv (fit) |
State values: | sx_params.csv (fit) |
Predictions: | px_params.csv (fit) |