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The reasons for this decision were
- Creating an saemix generic in the saemix package caused problems with
roxygen, because functions like saemix.plot.xy were documented in
their help files as S3 methods, although explicitly exported with
@export
- Creating an saemix generic in this package is possible, but would
make it necessary to load samix with exclude = "saemix" in order to
avoid overwriting the generic when loading saemix.
- The return object of such an saemix generic in this package cannot
be an S3 class with class attribute c("saemix.mmkin", "SaemixObject")
similar to nlme.mmkin, as saemix returns an S4 class.
- Extending the S4 class SaemixObject using simple inheritance to
a class SaemixMmkinObject with additional slots did not work
as expected. When the initialize method was left untouched, it
prevented creation of an SaemixMmkinObject even if it was based
on an initialised SaemixObject, as the initialize method seems
to always be called by new(). This could potentially be circumvented
by a coerce method. If an alternative initialize method was
used, an SaemixMmkinObject could be created. However, the methods
written for SaemixObjects only worked in some instances, either
because they checked for the class, and not for class inheritance
(like compare.saemix), or because the initialize method was called
for some reason. Therefore, the idea of creating a derived S4 class
was abandoned.
- A side effect of this decision is that the introduction of the saem
generic opens the possibility to use the same generic also for other
backends like nlmixr with the SAEM algorithm.
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Also, exclude the saemix function when loading saemix in the example
code, to prevent overriding our generic
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This commit also defined saemix.mmkin for mmkin row objects.
This works fine, but if we set the class of the returned object
to c("saemix.mmkin", "saemix"), it is not an S4 class any more
which make it impossible to use saemix functions on it.
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Also, use logit transformation for g and for solitary formation
fractions, addressing #10.
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Also commit the dontrun instruction for saemix I had wanted to commit
and switch back to devel mode for pkgdown
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Also, use more intelligent starting values for the variance of the
random effects for saemix. While this does not appear to speed up
the convergence, it shows where this variance is greatly reduced
by using mixed-effects models as opposed to the separate independent
fits.
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saemix_data depends on a development version of saemix, see
pull request saemixdevelopment/saemixextension#2
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