mkin/docs/reference/plot.mmkin.html, branch v0.9.49.10Fitting kinetic models to chemical degradation data (also on github)https://cgit.jrwb.de/mkin/atom?h=v0.9.49.102020-04-15T17:00:06ZInclude random effects in starting parameters2020-04-15T17:00:06ZJohannes Rankejranke@uni-bremen.de2020-04-15T16:13:04Zurn:sha1:42171ba55222383a0d47e5aacd46a972819e7812
- mean_degparms() now optionally returns starting values for fixed and
random effects, which makes it possible to obtain acceptable fits
also in more difficult cases (with more parameters)
- Fix the anova method, as it is currently not enough to inherit from
lme: https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17761
- Show fit information, and per default also errmin information
in plot.nlme.mmkin()
- Examples for nlme.mmkin: Decrease tolerance and increase the number of
iterations in the PNLS step in order to be able to fit FOMC-SFO and
DFOP-SFO
Improve nlme function docs2020-04-10T06:26:44ZJohannes Rankejranke@uni-bremen.de2020-04-10T06:26:44Zurn:sha1:7777ff3b019e54364947ff393e2dab782d7cfe3cCompiled models article, reduce distractions2020-04-03T08:53:07ZJohannes Rankejranke@uni-bremen.de2020-04-02T08:58:34Zurn:sha1:47ba9ea512b82fb8b31da8ec5558f3c0952d86d4
- 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()
Static documentation rebuilt by pkgdown2020-03-30T19:43:10ZJohannes Rankejranke@uni-bremen.de2020-03-30T19:43:10Zurn:sha1:575fcacaa33076de97f41a79afb37efb97ca82e0Argument ymax for plot.mmkin2019-12-16T01:51:19ZJohannes Rankejranke@uni-bremen.de2019-12-16T01:51:19Zurn:sha1:1868c1c6b98afa4c8a11b7c065d717bfb4ec1a8eStatic documentation rebuilt by pkgdown2019-10-25T00:10:08ZJohannes Rankejranke@uni-bremen.de2019-10-25T00:10:08Zurn:sha1:af2e1540cdad2fd00bb6216a38a754ff748629adCorrect and rebuild docs2019-09-18T11:03:50ZJohannes Rankejranke@uni-bremen.de2019-09-18T11:03:50Zurn:sha1:e05656d57668688b971c28e32b4cfd4d3eac4662
- Reconcile docs and code for max_twa_parent
- Correct links to docs in twa vignette
- Static documentation rebuilt by pkgdown
Static documentation rebuilt by pkgdown2019-07-05T13:57:24ZJohannes Rankejranke@uni-bremen.de2019-07-05T13:57:24Zurn:sha1:4596667b19f032232ceb8f3f762aaad5d69c15beAdditional algorithm "d_c", more tests, docs2019-06-04T13:09:28ZJohannes Rankejranke@uni-bremen.de2019-06-04T13:09:28Zurn:sha1:95178837d3f91e84837628446b5fd468179af2b9
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.
Add functionality to plot the error model2019-05-08T18:57:48ZJohannes Rankejranke@uni-bremen.de2019-05-08T18:57:48Zurn:sha1:c6079a807e2b400fe0c772603392aeacd887da2f
by plotting squared residuals against predicted values, and
showing the variance function used in the fitted error model.
Rebuild docs