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] = 0.5000
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

-276.7916

which required N. iterations and took 882.65 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 1.9129
f[V] = 20.2481
f[PNOISE_STD] = 0.2087
f[ANOISE_STD] = 0.0483
f[CL_isv] = 0.2392
f[CL_iov] = 0.0075

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]	1.9129	1.0000	0.9129	0.9129
f[V]	20.2481	15.0000	0.3499	5.2481

Compare Noise f[X]

Variable Name	Fitted Value	Starting Value	Prop Change	Abs Change
f[PNOISE_STD]	0.2087	0.2000	0.0435	0.0087
f[ANOISE_STD]	0.0483	0.2000	0.7583	0.1517

Compare Variance f[X]

Variable Name	Fitted Value	Starting Value	Prop Change	Abs Change
f[CL_isv]	0.2392	0.0100	22.9190	0.2292
f[CL_iov]	0.0075	0.0100	0.2514	0.0025