R: Calculate the minimum error to assume in order to pass the...
mkinerrmin
R Documentation
Calculate the minimum error to assume in order to pass the variance test
Description
This function uses optimize in order to iteratively find the
smallest relative error still resulting in passing the chi-squared test
as defined in the FOCUS kinetics report from 2006.
Usage
mkinerrmin(fit, alpha = 0.05)
Arguments
fit
an object of class mkinfit.
alpha
The confidence level chosen for the chi-squared test.
Details
This function is used internally by summary.mkinfit.
Value
A dataframe with the following components:
err.min
The relative error, expressed as a fraction.
n.optim
The number of optimised parameters attributed to the data series.
df
The 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.
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://focus.jrc.ec.europa.eu/dk