Diagonal matrix generation diagonal matrix fit using separate univariate normals

[Generated automatically as a Generation summary]

Model Description

Name:: gen_indep_fit_indep
Title:: Diagonal matrix generation diagonal matrix fit using separate univariate normals
Author:: PoPy for PK/PD
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_gen.pyml
Diagram:

Outputs

Individual simulated (sim) plots

Alternatively see All simulated_sim graph plots

Population simulated (sim) plots

allOBS_vs_TIME

Generated parameter .csv files

Fixed Effects:: fx_params.csv (gen)
Random Effects:: rx_params.csv (gen)
Model params:: mx_params.csv (gen)
State values:: sx_params.csv (gen)
Predictions:: px_params.csv (gen)
Observations:: synthetic_data.csv (gen)

Inputs

True f[X] values (for simulation)

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] = 0.2000
f[V_isv] = 0.1000