mkin/vignettes, branch v0.9.49.5Fitting kinetic models to chemical degradation data (also on github)https://cgit.jrwb.de/mkin/atom?h=v0.9.49.52019-07-04T06:10:33ZAddress failures of CRAN checks, improve NEWS2019-07-04T06:10:33ZJohannes Rankejranke@uni-bremen.de2019-07-04T06:10:33Zurn:sha1:7e8d788d298b8e1492fd8f62d88456e99e0f5992
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Update DESCRIPTION, improve NEWS2019-07-03T14:45:09ZJohannes Rankejranke@uni-bremen.de2019-07-03T14:45:09Zurn:sha1:798195d367111e592e5247309b90fac29ed7ddfd
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Merge branch 'algorithm'2019-06-05T15:03:19ZJohannes Rankejranke@uni-bremen.de2019-06-05T15:03:19Zurn:sha1:5243ac0ebe3223e5803b4ebee1cb619008638785Add error model algorithm to output2019-06-05T13:16:59ZJohannes Rankejranke@uni-bremen.de2019-06-05T13:16:59Zurn:sha1:b6027bbd157734e1c7f8c3ba6373451f5c85fc38Additional 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.
Typo2019-05-24T06:25:39ZJohannes Rankejranke@uni-bremen.de2019-05-24T06:25:39Zurn:sha1:b061a00ba4f9410a4b77e58a96fb7baa1247252bAdd 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
Fix hessian calculations2019-05-07T06:43:12ZJohannes Rankejranke@uni-bremen.de2019-05-07T06:43:12Zurn:sha1:c322a8102a399cbb1fe38c4c4ca4485cea8bc4e8
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After the OLS step, use OLS parameter estimates2019-05-07T06:12:27ZJohannes Rankejranke@uni-bremen.de2019-05-07T06:12:27Zurn:sha1:8a3475c59f3d91ce5ce7d980d6de09360617e7fe
- Fix the respective error in the code
- Static documentation rebuilt by pkgdown
Improve error model fitting2019-05-03T17:14:15ZJohannes Rankejranke@uni-bremen.de2019-05-03T17:14:15Zurn:sha1:1ef7008be2a72a0847064ad9c2ddcfa16b055482
Now we have a three stage fitting process for
nonconstant error models:
- Unweighted least squares
- Only optimize the error model
- Optimize both
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