Hi Kirsten,
Thanks for the info about the outdated link.
This should now be fixed in the devel version of IsoriX which you can install using remotes::install_github("courtiol/IsoriX/IsoriX")
For this to work, you may have to install the package remotes if it is not on your system: install.packages("remotes").
Please let me know if that works or not for you.
About the R2:
The calibration model fitted in IsoriX is a complex kind of errors-in-variables model.
Indeed,
when fitting the calibration curve we account for both the error
measurements in the sample but also for the uncertainty of the isoscape.
This
is why we don't provide an R2: under such a model, the R2 metric does
not reflect the quality of the fit and should not be used to compare
models.
An intuitive way to understand that is to think that
the fit doesn't try to maximise the relationship between predictions and
observations because observations associated with locations where the
isotopic values vary a lot are less important to get a good calibration
than locations where the isotopic values vary less.
What
would make more sense to compare models would be to perform cross
validation but since calibration models are usually slow to fit, that
would take forever...
IMO, reviewers asking for R2 are often reviewers that do not understand statistics very well.
They
want a R2 because they are used to the metric but they don't quite
understand what it means beyond paroting "it is the part of the variance
in prediction explained by the model".
Nor do they know when it makes sense to compute such a metric and when it does not.
Anyhow
don't tell them that ;-), but perhaps explain that the models fitted in
IsoriX are not simple linear regression for which the R2 has been
developed.
Thanks for using IsoriX!