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

-353.3355

which required 1.26 iterations and took 517.84 seconds

Final fitted fixed effects

f[KA] = 0.2711
f[CL] = 2.4007
f[V] = 18.3926
f[PNOISE_STD] = 0.0935
f[ANOISE_STD] = 0.0487
f[CL_isv] = 0.0829
f[CL_iov] = 0.1073

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	Starting Value	Fitted Value	Prop Change	Abs Change
f[KA]	0.5000	0.2711	0.4577	0.2289
f[CL]	1.0000	2.4007	1.4007	1.4007
f[V]	15.0000	18.3926	0.2262	3.3926

Compare Noise f[X]

Variable Name	Starting Value	Fitted Value	Prop Change	Abs Change
f[PNOISE_STD]	0.2000	0.0935	0.5325	0.1065
f[ANOISE_STD]	0.2000	0.0487	0.7566	0.1513

Compare Variance f[X]

Variable Name	Starting Value	Fitted Value	Prop Change	Abs Change
f[CL_isv]	0.0100	0.0829	7.2852	0.0729
f[CL_iov]	0.0100	0.1073	9.7323	0.0973