Age | Commit message (Collapse) | Author | Files | Lines |
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- Added a section with platform specific notes on getting compiled
models to work to the compiled models article
- Don't return empty SFORB parameter list from endpoints() if there is no
SFORB model
- Avoid warnings when using standardized = TRUE in plot.mmkin()
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Roxygen update -> formatting changes in Rd files
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instead of "two component error model"
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- Switch an example dataset in the test setup to a dataset with
replicates, adapt tests
- Skip the test for lrtest with an update specification as it does not
only fail when pkgdown generates static help pages, but also in testthat
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Also the documentation was improved here and there
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The likelihood ratio test method is lrtest, in addition,
methods for update and residuals were added.
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Static documentation rebuilt by pkgdown
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Only on Linux at the moment. Some more examples in the help page.
Remove the distribution argument for the quadratic method
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The cutoff now matches what is given by Venzon and Moolgavkar (1988).
Also, confidence intervals closely match intervals obtained with
stats4::confint in the test case where an stats4::mle object
is created from the likelihood function in one test case.
Static documentation rebuilt by pkgdown
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Static documentation rebuilt by pkgdown
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The confint method can do profile likelihood based confidence intervals!
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in the hope that this makes plotting cross-platform also for this error
model
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Static documentation rebuilt by pkgdown
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Static documentation rebuilt by pkgdown
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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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that I made in the first attempt to work around the issue with the %in%
operator in the example code
Static documentation rebuilt by pkgdown
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Use lazy = TRUE in the pd target for generating pkgdown documentation
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as it leads to problems with current pkgdown versions r-lib/pkgdown#1149
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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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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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in relation to the original version by Rocke and Lorenzato
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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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- 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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In order to avoid some unnecessary documentation rebuilds
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