• Language: en

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.2

[Generated automatically as a Fitting summary]

Inputs

Description

Name:dep_one_cmp_cl_iov
Title:One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.2
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-occasion Variance
Keywords:one compartment model; dep_one_cmp_cl; iov
Input Script:dep_one_cmp_cl_iov_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] = 0.0100
f[CL_iov] = 0.0100

Outputs

Final objective value

-276.3492

which required N. iterations and took 319.26 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 2.2364
f[V] = 20.9615
f[PNOISE_STD] = 0.2091
f[ANOISE_STD] = 0.0516
f[CL_isv] = 0.0732
f[CL_iov] = 0.0937

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] 2.2364 1.0000 1.2364 1.2364
f[V] 20.9615 15.0000 0.3974 5.9615

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.2091 0.2000 0.0453 0.0091
f[ANOISE_STD] 0.0516 0.2000 0.7420 0.1484

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[CL_isv] 0.0732 0.0100 6.3174 0.0632
f[CL_iov] 0.0937 0.0100 8.3730 0.0837
Back to Top