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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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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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- 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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- No IRLS required
- Removed optimization algorithms other than Port
- Removed the dependency on FME
- Fitting the error model 'obs' is much faster for the FOCUS_2006_D
dataset and the FOMC_SFO model (1 second versus 3.4 seconds)
- Vignettes build slower. Compiled models needs 3 minutes instead of 1.5
- For other vignettes, the trend is less clear. Some fits are faster,
even for error_model = "const". FOCUS_Z is faster (34.9 s versus
44.1 s)
- Standard errors and confidence intervals are slightly smaller
- Removed code for plotting during the fit, as I hardly ever used it
- Merged the two cost functions (using transformed and untransformed
parameters) into one log-likelihood function
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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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Static documentation rebuilt by pkgdown
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to avoid NOTES about long execution times.
Static documentation rebuilt by pkgdown with run_dont_run = TRUE
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Also improve the irls fitting of the error model and add a test
for FOCUS_2006_C where the second component of the error model is zero
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Rename 'sigma_rl' to 'sigma_twocomp' as the Rocke and Lorenzato model assumes lognormal distribution for large y.
Rebuild static documentation.
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Static documentation except articles rebuilt by pkgdown
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Static documentation except articles rebuilt by pkgdown
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- Typo in synthetic data for UBA
- Static documentation except articles rebuilt by pkgdown
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Static documentation except articles rebuilt by pkgdown
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Static documentation except articles rebuilt by pkgdown
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Static documentation except articles rebuilt by pkgdown
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as recommended, e.g. by Uwe Ligges in his useR! 2017 keynote
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- Fix the remaining links to static docs on r-forge in README
- Build mkin_*.tar.gz packages in current directory
- check and test (test.log unchanged)
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Again with the jranke branch of jranke/pkgdown
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The test test_FOMC_ill-defined leads to errors on several
architectures/distributions, as apparent from CRAN checks,
so we need a new release.
Static documentation rebuilt by staticdocs::build_site()
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Also a small fix to the FOCUS Z vignette, and an update
of the static documentation generated by staticdocs.
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mkinfit: Do not error out in cases where the fit converges, but the
Jacobian for the untransformed model cost can not be estimated. Give a
warning instead and return NA for the t-test results.
summary.mkinfit: Give a warning message when the covariance matrix can
not be obtained.
A test has been added to containing such an edge case to check that
the warnings are correctly issued and the fit does not terminate.
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- Now it is easier to do decline kinetics from the maximum occurrence
- Static documentation rebuilt by staticdocs::build_site()
- Fixed an URL in the README, thanks to the win-builder check with
R-devel
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r-forge
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