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Package smooth for R

“smooth” package for R. es() function. Part IV. Model selection and combination of forecasts

24.01.201709.08.2019 Leave a comment

Mixed models In the previous posts we have discussed pure additive and pure multiplicative exponential smoothing models. The next logical step would be to discuss mixed models, where some components have additive and the others have multiplicative nature. But we won’t spend much time on them because I personally think that they do not make […]

“smooth” package for R. es() function. Part III. Multiplicative models

18.11.201631.07.2019 Leave a comment

Theoretical stuff Last time we talked about pure additive models, today I want to discuss multiplicative ones. There is a general scepticism about pure multiplicative exponential smoothing models in the forecasters society, because it is not clear why level, trend, seasonality and error term should be multiplied. Well, when it comes to seasonality, then there […]

“smooth” package for R. es() function. Part II. Pure additive models

02.11.201631.07.2019 Leave a comment

A bit of statistics As mentioned in the previous post, all the details of models underlying functions of “smooth” package can be found in extensive documentation. Here I want to discuss several basic, important aspects of statistical model underlying es() and how it is implementated in R. Today we will have a look at basic […]

“smooth” package for R. es() function. Part I

14.10.201631.07.2019 Leave a comment

Good news, everyone! “smooth” package is now available on CRAN. And it is time to look into what this package can do and why it is needed at all. The package itself contains some documentation that you can use as a starting point. For example, there are vignettes, which show included functions and what they […]

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  • Ivan Svetunkov on Are you sure you’re precise? Measuring accuracy of point forecasts
  • Nicolas Vandeput on Are you sure you’re precise? Measuring accuracy of point forecasts
  • Fotios Petropoulos on M-competitions, from M4 to M5: reservations and expectations
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