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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: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

-276.596847289

which required N. iterations and took 903.48 seconds

Final fitted fixed effects

f[KA] = 1
f[CL] = 1.8485
f[V] = 20.257
f[PNOISE_STD] = 0.21347
f[ANOISE_STD] = 0.047715
f[CL_isv] = 0.27007
f[CL_iov] = 0.008566

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] 1.84847 1 0.848469 0.848469
f[V] 20.2568 15 0.350455 5.25682

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.213473 0.2 0.0673627 0.0134725
f[ANOISE_STD] 0.0477148 0.2 0.761426 0.152285

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[CL_isv] 0.27007 0.01 26.007 0.26007
f[CL_iov] 0.00856602 0.01 0.143398 0.00143398
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