# One Compartment Model with Absorption estimating KA, V and CL

[Generated automatically as a Fitting summary]

## Model Description

Name:

  d1cmp_ka_v_cl_stderr

Title:

  One Compartment Model with Absorption estimating KA, V and CL

Author:

  PoPy for PK/PD

Abstract:

One Compartment Model with Absorption compartment with rate (KA).
Elimination rate parametrised by clearance (CL)
and volume of distribution (V).
Model specification uses incremental flows

Keywords:

  dep_one_cmp_cl; one compartment model

Input Script:

  `d1cmp_ka_v_cl_stderr_fit.pyml`

Diagram:

## Comparison

### Compare Main f[X]

Variable Name | Starting Value | Fitted Value | Abs Change | Prop Change
--- | --- | --- | --- | ---
f[KA] | 0.3000 | 0.2738 | 0.0262 | 0.0872
f[V] | 20.0000 | 17.9983 | 2.0017 | 0.1001
f[CL] | 3.0000 | 3.2389 | 0.2389 | 0.0796

### Compare Noise f[X]

### Compare Variance f[X]

### Population simulated (sim) plots

| indOBS_vs_TIME

## Outputs

### Final objective value

    -44.7678

which required 1.7 iterations and took 10.72 seconds

### Fitted f[X] values (after fitting)

    f[KA] = 0.2738
    f[V] = 17.9983
    f[CL] = 3.2389

### 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)`

Likelihoods:

  `lx_params.csv (fit)`

## Inputs

Input Data:

  `cx_obs_params.csv`

### Starting f[X] values (before fitting)

    f[KA] = 0.3000
    f[V] = 20.0000
    f[CL] = 3.0000