mkin/_pkgdown.yml, branch v0.9.49.8 Fitting kinetic models to chemical degradation data (also on github) https://erac.jrwb.de/mkin/atom?h=v0.9.49.8 2019-11-13T20:15:35Z Calculate Akaike weights 2019-11-13T20:15:35Z Johannes Ranke jranke@uni-bremen.de 2019-11-13T20:15:35Z urn:sha1:c3700bec3a704660d3ade7a54c56b7084beb02b4 Add a lack-of-fit test 2019-11-09T00:05:51Z Johannes Ranke jranke@uni-bremen.de 2019-11-09T00:05:51Z urn:sha1:20b9c584e7c43ecbb708459e531c24a1a4751e17 - 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 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 Add likelihood ratio test and other methods, fixes 2019-10-31T00:59:05Z Johannes Ranke jranke@uni-bremen.de 2019-10-31T00:55:01Z urn:sha1:7091d3738e7e55acb20edb88772b228f6f5b6c98 The likelihood ratio test method is lrtest, in addition, methods for update and residuals were added. Fix checks and tests 2019-10-26T20:52:53Z Johannes Ranke jranke@uni-bremen.de 2019-10-26T20:52:53Z urn:sha1:6e5630a0df7e857697ff2ce4730a5f7f45b67377 Static documentation rebuilt by pkgdown Improve tests, remove geometric_mean 2019-10-21T13:31:59Z Johannes Ranke jranke@uni-bremen.de 2019-10-21T13:31:59Z urn:sha1:41a2a356bd9b61c90c04b47aee147bf837223028 Add url: tag to _pkgdown.yml 2019-09-18T16:01:23Z Johannes Ranke jranke@uni-bremen.de 2019-09-18T16:01:23Z urn:sha1:b2c75fa1f73167d3e3c9c7db1d561dd482090aab Static documentation rebuilt by pkgdown change to `superseded` 2019-06-19T13:20:56Z Will Beasley wibeasley@hotmail.com 2019-06-19T13:20:56Z urn:sha1:16ce026bca4c17d5042ad724f23b70d8a0e6a982 https://en.wiktionary.org/wiki/superseed 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. Static documentation rebuilt by pkgdown 2019-02-26T20:12:21Z Johannes Ranke jranke@uni-bremen.de 2019-02-26T20:12:21Z urn:sha1:10f2314d12bc1e1664b1ff1db015d1df9f7fbe34