mkin/docs/articles/mkin_files/figure-html, branch nlmixr Fitting kinetic models to chemical degradation data (also on github) https://cgit.jrwb.de/mkin/atom?h=nlmixr 2021-03-31T17:42:17Z Bug fix in plot.mkinfit 2021-03-31T17:42:17Z Johannes Ranke jranke@uni-bremen.de 2021-03-31T17:42:17Z urn:sha1:3a5463672c297b37c3c9135c8b144c48744c05d0 In residual plots, use xlab and xlim if appropriate 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 Add docs generated using released version 0.9.52 2020-05-27T05:12:51Z Johannes Ranke jranke@uni-bremen.de 2020-05-27T05:12:51Z urn:sha1:b5ee48a86e4b1d4c05aaadb80b44954e2e994ebc Avoid merge() and data.frame() in cost function 2020-05-11T03:18:32Z Johannes Ranke jranke@uni-bremen.de 2020-05-11T03:15:19Z urn:sha1:234c9059a95e104917e488a6ddd2313234a96cdc also for deSolve and eigenvalue based solutions. This noticeably increases performance for these methods, see test.log and benchmark vignette. 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. Better initials for error model parameters 2019-05-02T11:17:05Z Johannes Ranke jranke@uni-bremen.de 2019-05-02T11:17:05Z urn:sha1:70591022c07f0e8fb4dd67789b7c8d78af8ebc18 - Also make it possible to specify initial values for error model parameters. - Run tests - Rebuild docs Another rebuild of the static docs 2018-03-09T22:14:39Z Johannes Ranke jranke@uni-bremen.de 2018-03-09T22:14:39Z urn:sha1:0b677308e3ffbf742880f05cc54da469f3ecc854 Now with rbenchmark installed, to get results for the compiled_models vignette