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2019-07-09Address winbuilder R-devel warning about usageJohannes Ranke3-5/+39
2019-07-09Merge branch 'master' of kolab.jrwb.de:mkinJohannes Ranke0-0/+0
2019-07-09Adaptations for gmkinJohannes Ranke42-743/+969
Address winbuilder check problems, update check log, update of static docs
2019-07-08Adaptations for gmkinJohannes Ranke1-1/+3
2019-07-08Support summarizing older fitsJohannes Ranke6-17/+51
generated with mkin < 0.9.49.5
2019-07-05Static documentation rebuilt by pkgdownJohannes Ranke93-1032/+849
2019-07-04Update README and introductory vignetteJohannes Ranke5-45/+106
2019-07-04Address failures of CRAN checks, improve NEWSv0.9.49.5Johannes Ranke19-81/+91
Static documentation rebuilt by pkgdown
2019-07-03Skip a test on CRAN/winbuilderJohannes Ranke1-0/+1
The test uses multiple cores in order to complete within a reasonable time
2019-07-03Add check and test logsJohannes Ranke3-17/+9
2019-07-03Update DESCRIPTION, improve NEWSJohannes Ranke18-91/+91
Static documentation rebuilt by pkgdown
2019-07-02TypoJohannes Ranke1-1/+1
2019-06-20Merge pull request #8 from wibeasley/patch-1Johannes Ranke1-1/+1
change to `superseded`
2019-06-19change to `superseded`Will Beasley1-1/+1
https://en.wiktionary.org/wiki/superseed
2019-06-05Merge branch 'algorithm'Johannes Ranke159-495/+1198
2019-06-05Adapt tests to new algorithms and outputJohannes Ranke4-381/+14
One of the tests exceeded the number of iterations when using the d_3 error model algorithm, so only use "direct" in this case.
2019-06-05Add error model algorithm to outputJohannes Ranke17-110/+198
2019-06-04Fix a bug introduced in the last commitJohannes Ranke2-3/+5
2019-06-04For the d_3 algorithm, report which was better, if anyJohannes Ranke1-2/+13
2019-06-04Add sources for test data for better transparencyJohannes Ranke1-0/+55
2019-06-04Also wait for codecov...Johannes Ranke1-1/+1
2019-06-04Fix travis configuration (hopefully)Johannes Ranke1-1/+1
2019-06-04Let travis wait longer for the check to finishJohannes Ranke1-0/+4
2019-06-04Additional algorithm "d_c", more tests, docsJohannes Ranke156-528/+1233
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.
2019-06-04Algorithms direct, two-, three-, fourstep, IRLSJohannes Ranke2-14/+86
All of them are working now and allow for comparison Based on SFO, DFOP and HS fits to twelve test datasets, only the combination of direct and threestep is needed to find the lowest AIC
2019-06-03Status von Samstag morgen - untestedJohannes Ranke2-37/+105
2019-05-31Experimental data for finding error model algorithmJohannes Ranke2-0/+65
2019-05-24TypoJohannes Ranke1-1/+1
2019-05-23Fix a bug that could lead to wrong chi2 error levelsJohannes Ranke5-29/+32
2019-05-21Clarify the relation of the two-component error modelJohannes Ranke1-2/+3
in relation to the original version by Rocke and Lorenzato
2019-05-20Only use colors for error model "obs"Johannes Ranke1-3/+3
2019-05-14Don't use remote CRAN incoming checksJohannes Ranke1-1/+1
2019-05-08Add functionality to plot the error modelJohannes Ranke37-129/+600
by plotting squared residuals against predicted values, and showing the variance function used in the fitted error model. Rebuild docs
2019-05-07Fix hessian calculationsJohannes Ranke27-1164/+963
Static documentation rebuilt by pkgdown
2019-05-07After the OLS step, use OLS parameter estimatesJohannes Ranke31-1073/+1025
- Fix the respective error in the code - Static documentation rebuilt by pkgdown
2019-05-03Improve error model fittingJohannes Ranke49-592/+622
Now we have a three stage fitting process for nonconstant error models: - Unweighted least squares - Only optimize the error model - Optimize both Static documentation rebuilt by pkgdown
2019-05-02Build logJohannes Ranke1-1/+3
2019-05-02Remove reference to archived kinfit packageJohannes Ranke16-360/+1739
from vignettes/mkin.Rmd Static documentation rebuilt by pkgdown
2019-05-02Prepare for CRAN releaseJohannes Ranke18-98/+103
- Skip long running tests on CRAN as well to avoid timeout on winbuilder - Don't install benchmark results in the package, they are only needed in the git repository - Don't run example in man/add_err.Rd as it takes > 10 s on winbuilder - Rebuild docs
2019-05-02Improve testsJohannes Ranke5-34/+45
- Improve control of the number of cores - Reduce the precision of the correlation matrix in the test summary output, as the exact results are platform dependent
2019-05-02Better initials for error model parametersJohannes Ranke78-424/+450
- Also make it possible to specify initial values for error model parameters. - Run tests - Rebuild docs
2019-04-24Improve output and update testsJohannes Ranke7-112/+70
Remove skipped tests as I do not intend to reactivate them
2019-04-10Address failure on travisJohannes Ranke4-3/+4
Also reduce the digits in the representative half-live given by nafta()
2019-04-10Adapt tests, vignettes and examplesJohannes Ranke139-2333/+6813
- Write the NEWS - Static documentation rebuilt by pkgdown - Adapt mkinerrmin - Fix (hopefully all) remaining problems in mkinfit
2019-04-08Remove zero observations, adapt logLikJohannes Ranke2-24/+11
Zero observations at time zero made fitting the two-component error model fail. A concentration of exactly zero does not make sense anyways, as we generally have a limit of detection
2019-04-05Report negative log-likelihood during fitsJohannes Ranke1-4/+10
If not quiet = TRUE
2019-04-04Direct error model fitting worksJohannes Ranke10-666/+1876
- No IRLS required - Removed optimization algorithms other than Port - Removed the dependency on FME - Fitting the error model 'obs' is much faster for the FOCUS_2006_D dataset and the FOMC_SFO model (1 second versus 3.4 seconds) - Vignettes build slower. Compiled models needs 3 minutes instead of 1.5 - For other vignettes, the trend is less clear. Some fits are faster, even for error_model = "const". FOCUS_Z is faster (34.9 s versus 44.1 s) - Standard errors and confidence intervals are slightly smaller - Removed code for plotting during the fit, as I hardly ever used it - Merged the two cost functions (using transformed and untransformed parameters) into one log-likelihood function
2019-03-19Set URL to documentation pageJohannes Ranke1-1/+1
2019-03-04Update README.html for cgit.jrwb.deJohannes Ranke1-1/+1
2019-03-04Make some example output more reproducibleJohannes Ranke17-914/+177
In order to avoid some unnecessary documentation rebuilds

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