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

# }