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

[Generated automatically as a Fitting summary]

## Inputs

### Description

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

Population one Compartment Model with Absorption and Inter-occasion Variance

Keywords: | one compartment model; dep_one_cmp_cl; iov
Input Script: | `dep_one_cmp_cl_iov_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

    -276.188167113

which required N. iterations and took 697.05 seconds

### Final fitted fixed effects

    f[KA] = 1
    f[CL] = 2.211
    f[V] = 20.54
    f[PNOISE_STD] = 0.2123
    f[ANOISE_STD] = 0.05187
    f[CL_isv] = 0.073326
    f[CL_iov] = 0.10083

### 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] | 2.21102 | 1 | 1.21102 | 1.21102
f[V] | 20.5398 | 15 | 0.369319 | 5.53978

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[PNOISE_STD] | 0.212303 | 0.2 | 0.0615144 | 0.0123029
f[ANOISE_STD] | 0.0518701 | 0.2 | 0.74065 | 0.14813

### Compare Variance f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[CL_isv] | 0.0733258 | 0.01 | 6.33258 | 0.0633258
f[CL_iov] | 0.100826 | 0.01 | 9.08262 | 0.0908262