# 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

    -276.234851705

which required 26 iterations and took 149.41 seconds

### Final fitted fixed effects

    f[KA] = 1
    f[CL] = 2.2203
    f[V] = 20.724
    f[PNOISE_STD] = 0.21306
    f[ANOISE_STD] = 0.052026
    f[CL_isv] = 0.072757
    f[CL_iov] = 0.1003

### 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] | 2.2203 | 1 | 1.2203 | 1.2203
f[V] | 20.7242 | 15 | 0.381611 | 5.72416

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[PNOISE_STD] | 0.213057 | 0.2 | 0.0652843 | 0.0130569
f[ANOISE_STD] | 0.0520259 | 0.2 | 0.739871 | 0.147974

### Compare Variance f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[CL_isv] | 0.072757 | 0.01 | 6.2757 | 0.062757
f[CL_iov] | 0.100297 | 0.01 | 9.02969 | 0.0902969