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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] = 0.5
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

-276.188167113

which required N. iterations and took 697.05 seconds

Final fitted fixed effects

f[KA] = 1
f[CL] = 2.211
f[V] = 20.54
f[PNOISE_STD] = 0.2123
f[ANOISE_STD] = 0.05187
f[CL_isv] = 0.073326
f[CL_iov] = 0.10083

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] 2.21102 1 1.21102 1.21102
f[V] 20.5398 15 0.369319 5.53978

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.212303 0.2 0.0615144 0.0123029
f[ANOISE_STD] 0.0518701 0.2 0.74065 0.14813

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[CL_isv] 0.0733258 0.01 6.33258 0.0633258
f[CL_iov] 0.100826 0.01 9.08262 0.0908262
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