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I had to fix the two pathway vignettes, as they did not work with
the released version any more. So they and the multistart vignette
which got some small fixes as well were rebuilt.
Complete rebuild of the online docs with the released version. The
documentation of the 'hierarchial_kinetics' format had to be fixed
as well.
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This also adds the first benchmark results obtained on my laptop system
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I am postponing my attempts to get the nlmixr interface to CRAN, given
some problems with nlmixr using R-devel under Windows, see
https://github.com/nlmixrdevelopment/nlmixr/issues/596
and
https://github.com/r-hub/rhub/issues/512,
which is fixed by the removal of nlmixr from the testsuite.
For the tests to be more platform independent, the biphasic mixed
effects models test dataset was defined in a way that fitting
should be more robust (less ill-defined).
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In residual plots, use xlab and xlim if appropriate
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Also bump version to 1.0.3.
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- Improve authorship and copyright information
- Prepare pkgdown config
- Remove dependence on saemix as we need the development version which
is not ready for CRAN
- Temporarily remove saemix interface to check code coverage of the rest
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saemix_data depends on a development version of saemix, see
pull request saemixdevelopment/saemixextension#2
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also for deSolve and eigenvalue based solutions. This noticeably increases
performance for these methods, see test.log and benchmark vignette.
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The likelihood ratio test method is lrtest, in addition,
methods for update and residuals were added.
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mkinfit objects now include an ll() function to calculate the
log-likelihood. Part of the code was refactored, hopefully making it
easier to read and maintain. IRLS is currently the default algorithm for
the error model "obs", for no particular reason. This may be subject
to change when I get around to investigate.
Slow tests are now in a separate subdirectory and will probably
only be run by my own Makefile target.
Formatting of test logs is improved.
Roundtripping error model parameters works with a precision of 10% when
we use lots of replicates in the synthetic data (see slow tests). This
is not new in this commit, but as I think it is reasonable this
closes #7.
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Use lazy = TRUE in the pd target for generating pkgdown documentation
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to check if the link to the pfm package is correctly generated by
pkgdown after preparing the pfm package docs accordingly
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Static documentation rebuilt by pkgdown
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Static documentation rebuilt by pkgdown
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- Reconcile docs and code for max_twa_parent
- Correct links to docs in twa vignette
- Static documentation rebuilt by pkgdown
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Address winbuilder check problems, update check log, update of static docs
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Static documentation rebuilt by pkgdown
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Static documentation rebuilt by pkgdown
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The new algorithm tries direct optimization of the likelihood, as well
as a three step procedure. In this way, we consistently get the
model with the highest likelihood for SFO, DFOP and HS for all 12
new test datasets.
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by plotting squared residuals against predicted values, and
showing the variance function used in the fitted error model.
Rebuild docs
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Static documentation rebuilt by pkgdown
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- Fix the respective error in the code
- Static documentation rebuilt by pkgdown
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Now we have a three stage fitting process for
nonconstant error models:
- Unweighted least squares
- Only optimize the error model
- Optimize both
Static documentation rebuilt by pkgdown
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from vignettes/mkin.Rmd
Static documentation rebuilt by pkgdown
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- Skip long running tests on CRAN as well to avoid timeout on winbuilder
- Don't install benchmark results in the package, they are only needed
in the git repository
- Don't run example in man/add_err.Rd as it takes > 10 s on winbuilder
- Rebuild docs
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- Also make it possible to specify initial values for error model
parameters.
- Run tests
- Rebuild docs
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- Write the NEWS
- Static documentation rebuilt by pkgdown
- Adapt mkinerrmin
- Fix (hopefully all) remaining problems in mkinfit
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In order to avoid some unnecessary documentation rebuilds
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Static documentation rebuilt by pkgdown
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Also:
- Change rounding in print.nafta
- Add dots argument to nafta()
- Use cores=1 in examples
- Restrict N in IORE model to values > 0
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