Age | Commit message (Collapse) | Author | Files | Lines |
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I threw out mclapply as it did not play well with the linear algebra
routines used in the saemix code. Most of the change is actually
indentation in the code creating the model function. But there
is an important fix in mkinpredict which I had broken.
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The default is pdDiag again, as we often have a small number of datasets
in degradation kinetics.
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Depends on inline >= 0.16.2 (including the bug fixes from
eddelbuettel/inline#18), which provides 'moveDLL' to store the DLL for a
compiled function in a safe place in case the argument 'dll_dir' is
specified in the call to 'mkinmod'.
Huge thanks to Dirk @eddelbuettel for his review and support
for the work on the inline package.
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With automatic reloading in mkinfit and mkinpredict in case the
DLL is not loaded and the original DLL path has been cleaned up.
Depends on jranke/inline@974bdea04fcedfafaab231e6f359c88270b56cb9
See inline#13
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By depending on parallel instead of importing it, functions to set up
and stop a cluster are always available when mkin is loaded.
The use of multicore processing in mmkin on Windows is now documented in
the help file, which brings mkin closer to a version 1.0 #9.
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- D24_2014 dataset on aerobic soil degradation of 2,4-D from the EU
assessment as mkindsg object with metadata
- f_time_norm_focus() to do time-step normalisation using the FOCUS
method
- focus_soil_moisture data with default moisture contents at pF1,
pF 2 and pF 2.5 for USDA soil types from FOCUS GW guidance
- Dataset generation scripts in inst/dataset_generation
- Depend on R >= 2.15.1 in order to facilitate the use of
utils::globalVariables()
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which is now the default
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As can be seen in the miniscule change seen on R-devel in the reference
plot updated with this commit
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With a plot method. The class mixed.mmkin is currently only a virtual
class created to unify the plotting method.
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This avoids code duplication
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Currently SFO-SFO and DFOP-SFO. Speed increase factor about 60
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Also make the endpoints function work for saem objects.
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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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Do not give starting values for random effects in nlme.mmkin.
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Improve and update docs
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Update docs
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And add output for nlme fit translating the mkinfit error model "obs"
into nlme::varIdent().
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The experimental nlme version in my drat repository contains the
variance function structure varConstProp which makes it possible to use
the two-component error model in generalized nonlinear models using
nlme::gnls() and in mixed effects models using nlme::nlme().
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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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- Reduce significant digits for the objective function output in
mkinfit(..., quiet = FALSE) as R and R-devel gave different output on my
system
- Add makefile target 'devtest' for testing with R-devel, in order
to fix problems showing up with R-devel on Travis
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This revealed a bug in the data returned in mkinfit$data in the case
of the d_3 algorithm, which also affected the residual plot - the
data from the direct fitting was not returned even if this was
the better method.
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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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