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

-275.4309

which required 33 iterations and took 92.42 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 2.1808
f[V] = 19.7903
f[PNOISE_STD] = 0.2151
f[ANOISE_STD] = 0.0508
f[CL_isv] = 0.0741
f[CL_iov] = 0.1014

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]	2.1808	1.0000	1.1808	1.1808
f[V]	19.7903	15.0000	0.3194	4.7903

Compare Noise f[X]

Variable Name	Fitted Value	Starting Value	Prop Change	Abs Change
f[PNOISE_STD]	0.2151	0.2000	0.0755	0.0151
f[ANOISE_STD]	0.0508	0.2000	0.7461	0.1492

Compare Variance f[X]

Variable Name	Fitted Value	Starting Value	Prop Change	Abs Change
f[CL_isv]	0.0741	0.0100	6.4118	0.0641
f[CL_iov]	0.1014	0.0100	9.1392	0.0914