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Principles of Business Forecasting 2e

I recently got my hands on a physical copy of my new book: Principles of Business Forecasting (2nd edition). Ord, K., Fildes, R. and Kourentzes, N., 2017. Principles of business forecasting. 2nd ed. Wessex Press Publishing Co. I was invited by Keith Ord and Robert Fildes to join them in writing the much-revised 2nd edition… Read More »

Towards the “one-number forecast”

1. Introductory remarks One of the recurrent topics in online discussions on sales forecasting and demand planning is the idea of the “one-number forecast”, that is a common view of the future on which multiple plans and decisions can be made, from different functions of an organisation. In principle, this is yet another idea around… Read More »

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 »

R package: tsutils

The tsutils package for R includes functions that help with time series exploration and forecasting, that were previously included in the TStools package that is only available on github. The name change was necessary as there is another package on CRAN with the same name. The objective of TStools is to provide a development and… Read More »

Incorporating Leading Indicators into your Sales Forecasts

Nikolaos Kourentzes and Yves Sagaert, Foresight: The International Journal of Applied Forecasting, 2018, Issue 48. This is a modified version of the paper that appears in Foresight issue 48. This provides a simplified version of the modelling methodology described in this paper and applied here and here. Introduction Using leading indicators for business forecasting has… Read More »