# 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] = 0.5
    f[CL] = 1
    f[V] = 15
    f[PNOISE_STD] = 0.2
    f[ANOISE_STD] = 0.2
    f[CL_isv] = 0.01

## Outputs

### Final objective value

    -311.996254196

which required 31 iterations and took 146.40 seconds

### Final fitted fixed effects

    f[KA] = 1
    f[CL] = 2.4567
    f[V] = 22.048
    f[PNOISE_STD] = 0.23467
    f[ANOISE_STD] = 0.03752
    f[CL_isv] = 0.1284

### 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] | 2.45673 | 1 | 1.45673 | 1.45673
f[V] | 22.0483 | 15 | 0.469884 | 7.04826

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[PNOISE_STD] | 0.234672 | 0.2 | 0.173361 | 0.0346722
f[ANOISE_STD] | 0.0375202 | 0.2 | 0.812399 | 0.16248

### Compare Variance f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[CL_isv] | 0.128403 | 0.01 | 11.8403 | 0.118403