# One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

[Generated automatically as a Fitting summary]

## Inputs

### Description

Name: | d1cmp_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: | `d1cmp_cl_iov_05_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
    f[CL_iov] = 0.0100

## Outputs

### Final objective value

    -384.2726

which required 1.28 iterations and took 1298.79 seconds

### Final fitted fixed effects

    f[KA] = 0.3156
    f[CL] = 2.3649
    f[V] = 19.7233
    f[PNOISE_STD] = 0.0984
    f[ANOISE_STD] = 0.0486
    f[CL_isv] = 0.3028
    f[CL_iov] = 0.0029

### 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 | 0.3156 | 0.3689 | 0.1844
f[CL] | 1.0000 | 2.3649 | 1.3649 | 1.3649
f[V] | 15.0000 | 19.7233 | 0.3149 | 4.7233

### Compare Noise f[X]

Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[PNOISE_STD] | 0.2000 | 0.0984 | 0.5081 | 0.1016
f[ANOISE_STD] | 0.2000 | 0.0486 | 0.7569 | 0.1514

### Compare Variance f[X]

Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[CL_isv] | 0.0100 | 0.3028 | 29.2826 | 0.2928
f[CL_iov] | 0.0100 | 0.0029 | 0.7095 | 0.0071