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

[Generated automatically as a Fitting summary]

Inputs

Description

Name:d1cmp_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:d1cmp_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

-384.2726

which required 1.26 iterations and took 833.45 seconds

Final fitted fixed effects

f[KA] = 0.3156
f[CL] = 2.3644
f[V] = 19.7231
f[PNOISE_STD] = 0.0984
f[ANOISE_STD] = 0.0486
f[CL_isv] = 0.3029
f[CL_iov] = 0.0029

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 0.3156 0.3689 0.1844
f[CL] 1.0000 2.3644 1.3644 1.3644
f[V] 15.0000 19.7231 0.3149 4.7231

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE_STD] 0.2000 0.0984 0.5081 0.1016
f[ANOISE_STD] 0.2000 0.0486 0.7569 0.1514

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[CL_isv] 0.0100 0.3029 29.2857 0.2929
f[CL_iov] 0.0100 0.0029 0.7094 0.0071
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