This function finds the smallest relative error still resulting in passing the
chi-squared test as defined in the FOCUS kinetics report from 2006.

mkinerrmin(fit, alpha = 0.05)

## Arguments

fit |
an object of class `mkinfit` . |

alpha |
The confidence level chosen for the chi-squared test. |

## Value

A dataframe with the following components:

err.minThe relative error, expressed as a fraction.

n.optimThe number of optimised parameters attributed to the data series.

dfThe number of remaining degrees of freedom for the chi2 error level
calculations. Note that mean values are used for the chi2 statistic and
therefore every time point with observed values in the series only counts
one time.

The dataframe has one row for the total dataset and one further row for
each observed state variable in the model.

## Details

This function is used internally by `summary.mkinfit`

.

## References

FOCUS (2006) “Guidance Document on Estimating Persistence and
Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
Registration” Report of the FOCUS Work Group on Degradation Kinetics,
EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

## Examples

#> Successfully compiled differential equation model from auto-generated C code.

#> Warning: Observations with value of zero were removed from the data

#> err.min n.optim df
#> All data 0.0640 4 15
#> parent 0.0646 2 7
#> m1 0.0469 2 8

#> err.min n.optim df
#> All data 0.1544 4 13
#> parent 0.1659 2 7
#> m1 0.1095 2 6