One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

[Generated automatically as a Fitting summary]

Inputs

Description

Name:dep_one_cmp_cl_iov_05 Title:One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5 Author:Wright Dose Ltd Abstract:

Population one Compartment Model with Absorption and Inter-occasion Variance

Here f[CL_isv] true value is 0.5

Keywords:one compartment model; dep_one_cmp_cl; iov Input Script:dep_one_cmp_cl_iov_05_fit.pyml Input Data:synthetic_data.csv Diagram:

Initial fixed effect estimates

f[KA] = 0.5
f[CL] = 1
f[V] = 15
f[PNOISE_STD] = 0.2
f[ANOISE_STD] = 0.2
f[CL_isv] = 0.01
f[CL_iov] = 0.01

Outputs

Final objective value

-276.596757751

which required 24 iterations and took 130.74 seconds

Final fitted fixed effects

f[KA] = 1
f[CL] = 1.8513
f[V] = 20.269
f[PNOISE_STD] = 0.21367
f[ANOISE_STD] = 0.047704
f[CL_isv] = 0.26995
f[CL_iov] = 0.0085567

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	0.5	1	0.5
f[CL]	1.85134	1	0.851343	0.851343
f[V]	20.2693	15	0.351284	5.26926

Compare Noise f[X]

Variable Name	Fitted Value	Starting Value	Prop Change	Abs Change
f[PNOISE_STD]	0.213669	0.2	0.0683461	0.0136692
f[ANOISE_STD]	0.0477045	0.2	0.761478	0.152296

Compare Variance f[X]

Variable Name	Fitted Value	Starting Value	Prop Change	Abs Change
f[CL_isv]	0.269953	0.01	25.9953	0.259953
f[CL_iov]	0.00855672	0.01	0.144328	0.00144328