greybox v0.2.2 (Release data: 2018-05-25)
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Changes:
* New description of the package and badges in README.md
* New function - determination() - returns R-squares for the provided data. This can be useful when you need to analyse the multicollinearity effect.
* nParam method for logLik class.
* BICc - new method for the classes, implementing, guess what?
* Updated description of the package in the help file.
* ro() now returns a class and has print and plot methods associated with it.
* ro() is much more flexible now, returning whatever you want in an adequate format.
* New methods for the greybox functions: confint, vcov.
* Renamed "combiner" into "lmCombine", because it makes more sense. We will use "combine" name for a more general function that would combine forecasts from arbitrary provided models (e.g. smooth, forecast and lm classes).
Bugfixes:
* sigma() method returned the wrong standard error in cases of combined models.
greybox v0.2.1 (Release data: 2018-05-01)
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Changes:
* New description of the package and badges in README.md
greybox v0.2.1 (Release data: 2018-05-01)
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Changes:
* print.summary now specifies digits. Summary does not round up anything. This corresponds to the normal behaviour of these methods.
* Implemented Laplace distribution, which is useful when models are estimated using MAE.
* Sped up qs() and qlaplace() functions using the inverse cumulative functions.
* New function - ro() - Rolling origin.
Bugfixes:
* qs() returned weird values when several 0 and 1 were specified as probabilities.
greybox v0.2.0 (Release data: 2018-03-10)
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Changes:
* combiner now uses a more clever mechanism in case of bruteForce==FALSE.
* combiner now also checks if the provided data has ncol>nrow and sets bruteForce if it has.
* Use Kendall Tau as default in cor() for stepwise.
* Don't use Kendall Tau as default everywhere - only for fat regressions.
* New summary and print methods for models from stepwise. No statistical tests printed, only confidence intervals and ICs.
* AICc for smooth functions in case of iSS models should take only the demand sizes into account, not all the parameters.
greybox v0.1.1 (Release data: 2018-03-05)
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Changes:
* We now do not depend on smooth. We suggest it. It's smooth that should depend on greybox!
* New function imported from smooth - AICc.
* New functions for the S distribution (the maximisation of likelihood of which corresponds to the minimum of HAM): ds, ps, qs, rs.
* stepwise now returns the object of two classes: greybox and lm.
* combiner now returns three classes: greybox, lm and greyboxC.
* nParam is moved to greybox from smooth.
Bugfixes:
* If smooth is not installed, plot forecasts using simpler function.
* The forecasts are now produced for the combined models in cases of fat regressions.
greybox v0.1.0 (Release data: 2018-03-03)
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* Initial release. stepwise() and xregExpander() are imported here from smooth package.
* combiner() function that combines lm() models. This thing is in the development right now.
* combiner() has a meaningful summary() now. Working to make it more accesible to lm functions.
* summary() for combiner now returns the list of values.
* stepwise() should now perform slightly better.
* combiner() can now be smart and use stepwise for the models pool creation.
* combined lm model can now be used together with predict() and forecast() functions.
* plot() and forecast() methods for the combined functions.