# One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

[Generated automatically as a Fitting summary]

## Inputs

### Description

Name: | dep_one_cmp_cl_isv
Title: | One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2
Author: | Wright Dose Ltd
Abstract: |

Population one Compartment Model with Absorption and Inter-subject Variance

Keywords: | one compartment model; dep_one_cmp_cl
Input Script: | `dep_one_cmp_cl_isv_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

## Outputs

### Final objective value

    -371.3278

which required 1.21 iterations and took 459.50 seconds

### Final fitted fixed effects

    f[KA] = 0.2643
    f[CL] = 2.7416
    f[V] = 19.1995
    f[PNOISE_STD] = 0.1131
    f[ANOISE_STD] = 0.0417
    f[CL_isv] = 0.1648

### 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 | 0.2643 | 0.4715 | 0.2357
f[CL] | 1.0000 | 2.7416 | 1.7416 | 1.7416
f[V] | 15.0000 | 19.1995 | 0.2800 | 4.1995

### Compare Noise f[X]

Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[PNOISE_STD] | 0.2000 | 0.1131 | 0.4345 | 0.0869
f[ANOISE_STD] | 0.2000 | 0.0417 | 0.7916 | 0.1583

### Compare Variance f[X]

Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[CL_isv] | 0.0100 | 0.1648 | 15.4784 | 0.1548