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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
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