Tag Archives: R

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 »

Workshop on `Forecasting with R’

Fotios Petropoulos and I will be giving a workshop on how to produce forecasts using R. The focus will be on business forecasting applications and the workshop is part of the workshop series that runs as part of the 36th International Symposium on Forecasting on the 19th of June 2016. This workshop will provide a… 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 »

The Bias Coefficient: a new metric for forecast bias

In this post I introduce a new bias metric that has several desirable properties over traditional ones. When evaluating forecasting performance it is important to look at two elements: forecasting accuracy and bias. Although there has been substantial progress in the measurement of accuracy with various metrics being proposed, there has been rather limited progress… Read More »

Experimenting with Shiny for R

Shiny is a web application framework for R. The idea is simple: deploy R code in webpages. This might prove useful when user interaction is required, for instance to design and deploy forecasting experiments that need human participants. I gave it a try to see how easy is it to build a demo. Assuming your… Read More »

MAPA and intermittent demand forecasting

Recently I posted about a paper I co-authored with Fotios Petropoulos, now in JORS: Forecast Combinations for Intermittent Demand. There we found that for intermittent demand data using multiple levels of temporal aggregation, forecasting them with the appropriate models and finally combining the forecasts performed best. This approach has many analogies with the MAPA algorithm… Read More »