- Language: en
Diagonal matrix generation diagonal matrix fit using separate univariate normals¶
[Generated automatically as a Fitting summary]
Inputs¶
Description¶
| Name: | gen_indep_fit_indep |
|---|---|
| Title: | Diagonal matrix generation diagonal matrix fit using separate univariate normals |
| Author: | Wright Dose Ltd |
| Abstract: |
One compartment model with absorption compartment and CL/V parametrisation.
This script uses a diagonal covariance matrix to generate the data and a diagonal covariance matrix to fit.
Note here the ‘diagonal matrix’ is implemented as two separate univariate normal distributions, which is equivalent.
| Keywords: | dep_one_cmp_cl; one compartment model; diagonal matrix |
|---|---|
| Input Script: | gen_indep_fit_indep_fit.pyml |
| Input Data: | synthetic_data.csv |
| Diagram: |
Initial fixed effect estimates¶
f[KA] = 0.3
f[CL] = 3
f[V] = 20
f[PNOISE_STD] = 0.1
f[ANOISE_STD] = 0.05
f[CL_isv] = 0.01
f[V_isv] = 0.01
Outputs¶
Final fitted fixed effects¶
f[KA] = 0.3
f[CL] = 3
f[V] = 20
f[PNOISE_STD] = 0.1
f[ANOISE_STD] = 0.05
f[CL_isv] = 0.175
f[V_isv] = 0.087425
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) |
