One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0

[Generated automatically as a Fitting summary]

Inputs

Description

Name:dep_one_cmp_cl_isv_naive
Title:One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-subject Variance
Here f[CL_isv] is not estimated it is set to zero.
Keywords:one compartment model; dep_one_cmp_cl
Input Script:dep_one_cmp_cl_isv_naive_fit.pyml
Input Data:synthetic_data.csv
Diagram:

Initial fixed effect estimates

f[KA] = 0.5000
f[CL] = 1.0000
f[V] = 15.0000
f[PNOISE_STD] = 0.2000
f[ANOISE_STD] = 0.2000
f[CL_isv] = 0.0000

Outputs

Final objective value

-144.9255

which required N. iterations and took 82.62 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 2.4130
f[V] = 28.3507
f[PNOISE_STD] = 0.5950
f[ANOISE_STD] = 0.1184
f[CL_isv] = 0.0000

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]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[KA] 1.0000 0.5000 1.0000 0.5000
f[CL] 2.4130 1.0000 1.4130 1.4130
f[V] 28.3507 15.0000 0.8900 13.3507

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.5950 0.2000 1.9748 0.3950
f[ANOISE_STD] 0.1184 0.2000 0.4081 0.0816

Compare Variance f[X]