mkin/docs/reference/plot.mmkin-4.png, branch v1.0.3 Fitting kinetic models to chemical degradation data (also on github) https://erac.jrwb.de/mkin/atom?h=v1.0.3 2021-02-15T14:20:53Z Improve README, introductory vignette and some other docs 2021-02-15T14:20:53Z Johannes Ranke jranke@uni-bremen.de 2021-02-15T13:08:13Z urn:sha1:a9427a09abdf7ce9aaeae7c7190f90c8f2e5ef52 Also bump version to 1.0.3. Prepare for v1.0.0 2021-02-03T17:18:19Z Johannes Ranke jranke@uni-bremen.de 2021-02-03T15:41:31Z urn:sha1:f0ef23a7598e5d19648ae4edc2b74e0fba27a41c - Improve authorship and copyright information - Prepare pkgdown config - Remove dependence on saemix as we need the development version which is not ready for CRAN - Temporarily remove saemix interface to check code coverage of the rest Update online docs for release version 2020-10-15T10:53:23Z Johannes Ranke jranke@uni-bremen.de 2020-10-15T10:53:23Z urn:sha1:5b1179f0daff9077e1370065f9b9f03a2d0e0450 Include random effects in starting parameters 2020-04-15T17:00:06Z Johannes Ranke jranke@uni-bremen.de 2020-04-15T16:13:04Z urn: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 Fix bug in yesterdays release, add methods for BIC 2019-11-01T11:19:03Z Johannes Ranke jranke@uni-bremen.de 2019-11-01T11:19:03Z urn:sha1:bbb74d4f60033899cd5cdd36aa70f157bc52209e Static documentation rebuilt by pkgdown 2019-10-25T00:10:08Z Johannes Ranke jranke@uni-bremen.de 2019-10-25T00:10:08Z urn:sha1:af2e1540cdad2fd00bb6216a38a754ff748629ad Additional algorithm "d_c", more tests, docs 2019-06-04T13:09:28Z Johannes Ranke jranke@uni-bremen.de 2019-06-04T13:09:28Z urn: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 model 2019-05-08T18:57:48Z Johannes Ranke jranke@uni-bremen.de 2019-05-08T18:57:48Z urn:sha1:c6079a807e2b400fe0c772603392aeacd887da2f by plotting squared residuals against predicted values, and showing the variance function used in the fitted error model. Rebuild docs Static documentation rebuilt using current pkgdown::build_site() 2018-03-01T13:32:46Z Johannes Ranke jranke@uni-bremen.de 2018-03-01T13:32:46Z urn:sha1:6653ff2507f45eae909f491a9af3f1eb5358a600 Static documentation except articles rebuilt by pkgdown 2017-09-07T06:32:41Z Johannes Ranke jranke@uni-bremen.de 2017-09-07T06:32:41Z urn:sha1:7b333cff452dd1b36cb994c18b0b19e97facbc72