Age | Commit message (Collapse) | Author | Files | Lines |
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This increases performance up to a factor of five!
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Preparing for symbolic solutions for more than one compound
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The likelihood ratio test method is lrtest, in addition,
methods for update and residuals were added.
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in the hope that this makes plotting cross-platform also for this error
model
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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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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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- 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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Further relax two tests to pass build on Travis
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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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- Use quiet= TRUE in dontrun sections
- Use mkinsub in model definitions
- Avoid \code{\link{}} in titles
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Using branch 'jranke' on jranke/pkgdown, fixing issues
hadley/pgkdown#178 and hadley/pkgdown#213
Remove plot=TRUE from mkinfit calls also in dontrun sections of examples
to avoid a flood png files documenting the progress of the fit.
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Also ignore test.R in the top level directory, as it is not meant to
be public
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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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As it is unclear if and when ccSolve will be published on CRAN,
the generation, compilation and use of the C version of the
system of differential equations was developed for mkin, inspired and
guided by the code from the ccSolve package. Many thanks again to
Karline Soetaert for all of her work on this and other R packages.
Now all model types, including the Hockey-Stick model for the parent
compund and the IORE model for parent and/or metabolites can be compiled.
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Tests all pass (Linux)
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If the ccSolve package is available, and time is not in the right hand
side of the equations (i.e. if only SFO and SFORB models are used),
the differential equation model is compiled from auto-generated C code.
Currently, one test (FOCUS 2006 D SFO_SFO) fails
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- The bug occurred when using transform_rates=FALSE for FOMC, DFOP or HS
- Make it possible to use mkinfit("SFO", ...)
- Take initial mean value at time zero for the variable with the highest
value in the observed data
- Update of vignette/FOCUS_L
- Improve the Makefile to build single vignettes
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