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2020-11-09Some work on example code, pkgdown updateJohannes Ranke1-2/+7
2020-11-09Custom analytical solutions for saemixJohannes Ranke1-39/+107
Currently SFO-SFO and DFOP-SFO. Speed increase factor about 60
2020-11-08The call to saemix.predict fails with DFOP-SFOJohannes Ranke1-3/+3
2020-11-08Improve saem method, add summaryJohannes Ranke1-6/+31
Also make the endpoints function work for saem objects.
2020-11-07Create saem generic for fitting saemix modelsJohannes Ranke1-40/+45
The reasons for this decision were - Creating an saemix generic in the saemix package caused problems with roxygen, because functions like saemix.plot.xy were documented in their help files as S3 methods, although explicitly exported with @export - Creating an saemix generic in this package is possible, but would make it necessary to load samix with exclude = "saemix" in order to avoid overwriting the generic when loading saemix. - The return object of such an saemix generic in this package cannot be an S3 class with class attribute c("saemix.mmkin", "SaemixObject") similar to nlme.mmkin, as saemix returns an S4 class. - Extending the S4 class SaemixObject using simple inheritance to a class SaemixMmkinObject with additional slots did not work as expected. When the initialize method was left untouched, it prevented creation of an SaemixMmkinObject even if it was based on an initialised SaemixObject, as the initialize method seems to always be called by new(). This could potentially be circumvented by a coerce method. If an alternative initialize method was used, an SaemixMmkinObject could be created. However, the methods written for SaemixObjects only worked in some instances, either because they checked for the class, and not for class inheritance (like compare.saemix), or because the initialize method was called for some reason. Therefore, the idea of creating a derived S4 class was abandoned. - A side effect of this decision is that the introduction of the saem generic opens the possibility to use the same generic also for other backends like nlmixr with the SAEM algorithm.
2020-11-07Make deSolve predictions within saemix robustJohannes Ranke1-13/+23
Also, exclude the saemix function when loading saemix in the example code, to prevent overriding our generic
2020-11-06Make saemix an S3 generic in this packageJohannes Ranke1-42/+72
This commit also defined saemix.mmkin for mmkin row objects. This works fine, but if we set the class of the returned object to c("saemix.mmkin", "saemix"), it is not an S4 class any more which make it impossible to use saemix functions on it.
2020-11-06Fast analytical solutions for saemix, update.mmkinJohannes Ranke1-76/+137
Also, use logit transformation for g and for solitary formation fractions, addressing #10.
2020-11-04Update dynamic docsJohannes Ranke1-5/+6
2020-11-04Deprecate cores > 1 in saemix_modelJohannes Ranke1-3/+5
2020-10-15More gentle example for saemix with combined error modelJohannes Ranke1-1/+2
2020-10-15Don't run saemix examples on travis for nowJohannes Ranke1-1/+2
2020-10-15Updating docs of current dev versionJohannes Ranke1-1/+41
2020-10-15Reintroduce saemix helper functionsJohannes Ranke1-0/+134
2020-10-08Avoid dep on dev version of saemix for releaseJohannes Ranke1-134/+0
2020-05-26Use all cores per default, confint toleranceJohannes Ranke1-7/+24
Also, use more intelligent starting values for the variance of the random effects for saemix. While this does not appear to speed up the convergence, it shows where this variance is greatly reduced by using mixed-effects models as opposed to the separate independent fits.
2020-05-25Tell travis where to find the required saemix versionJohannes Ranke1-6/+5
2020-05-25First working version of saemix helper functionsJohannes Ranke1-0/+118
saemix_data depends on a development version of saemix, see pull request saemixdevelopment/saemixextension#2

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