Tag Archives: code

Tutorial for the nnfor R package

The nnfor (development version here) package for R facilitates time series forecasting with Multilayer Perceptrons (MLP) and Extreme Learning Machines (ELM). Currently (version 0.9.6) it does not support deep learning, though the plan is to extend this to this direction in the near future. Currently, it relies on the neuralnet package for R, which provides… Read More »

nnfor on github

I have put up a github repository for the nnfor package for R: https://github.com/trnnick/nnfor I will be putting updates and fixes there, before they are pushed on CRAN. You can also report there bugs. You can install the current github version with: Related PostsPrinciples of Business Forecasting 2e Benchmarking Facebook’s Prophet Forecasting time series with… Read More »

MAPAx available for R & new MAPA package on CRAN

The previous version of the MAPA package implemented only the univariate aspect of the algorithm. Version 2.0.1 implements MAPAx as well, which allows incorporating regressors in your forecasts. In this paper we demonstrated the usefulness of temporal aggregation in the case of forecasting demand in the presence of promotions. In particular, we showed that MAPAx… Read More »

MAPA package for R on GitHub

Here is the link: https://github.com/trnnick/mapa It has been a long time I wanted to rework the MAPA package for R, but I could not find the time. Finally I got around starting it. There are three objectives in this: Clean up code and introduce S3methods. MAPA was the first package that I wrote! Incorporate the… Read More »

TStools recent changes

We have been re-working the TStools package over the past couple of weeks. The major changes are: The es function that is an alternative to the ets function from the forecast package has been removed. Now it is published separately in the smooth package, which contains a collection of interesting implementations for exponential smoothing, ARIMA… Read More »

Material for `Forecasting with R: A practical workshop”

Together with Fotios Petropoulos we gave a workshop on producing forecasts with R, at the International Symposium on Forecasting, 2016. You can find the material of the workshop here. The workshop notes assume knowledge of what the various forecasting methods do, which are only briefly explained in the workshop’s slides, and mostly focuses in showing… Read More »

Another update for tsintermittent

Version 1.8 of tsintermittent has been submitted to CRAN and should be shortly available for download. Amongst various new checks on inputs to better accommodate handling multiple time series with data frames, a new option has been added to data.frc. When method=”auto” two things will happen: Function idclass(…,type=”PKa”) will be called to classify the time… Read More »