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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

-276.596757751

which required 24 iterations and took 130.74 seconds

Final fitted fixed effects

f[KA] = 1
f[CL] = 1.8513
f[V] = 20.269
f[PNOISE_STD] = 0.21367
f[ANOISE_STD] = 0.047704
f[CL_isv] = 0.26995
f[CL_iov] = 0.0085567

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] 1.85134 1 0.851343 0.851343
f[V] 20.2693 15 0.351284 5.26926

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.213669 0.2 0.0683461 0.0136692
f[ANOISE_STD] 0.0477045 0.2 0.761478 0.152296

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[CL_isv] 0.269953 0.01 25.9953 0.259953
f[CL_iov] 0.00855672 0.01 0.144328 0.00144328
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