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This revealed that transforming rates is necessary for fitting
the analytical solution of the SFO-SFO model to the FOCUS D dataset.
Benchmarks show that fitting coupled models with deSolve got a bit
slower through the latest changes
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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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