The creation of ADAM – next step in statistical forecasting

Good news everyone! The future of statistical forecasting is finally here :). Have you ever struggled with ETS and needed explanatory variables? Have you ever needed to unite ARIMA and ETS? Have you ever needed to deal with all those zeroes in the data? What about the data with multiple seasonalities? All of this and … Read more

SMUG2019

I was recently invited to attend the SMUG2019 conference (SMoothie Users Group), organised by Demand Works company in New York. They asked me to present two topics: State space ARIMA for Supply Chain Forecasting, based on which I have developed a module for Smoothie a couple of years ago, Artificial Intelligence in Business, one of … Read more

A simple combination of univariate models

Fotios Petropoulos and I have participated last year in M4 competition. Our approach performed well, finishing as 6th in the competition. This paper in International Journal of Forecasting explains what we used in our approach and why. Here’s the abstract: This paper describes the approach that we implemented for producing the point forecasts and prediction … Read more

State space ARIMA for supply-chain forecasting

John Boylan and I have been working lately on a paper, explaining the logic behind the ssarima() function from the smooth package. This paper has finally been accepted and published. Also, based on a modified version of the ssarima() function, I have developed a SSARIMA module for Smoothie software, developed by DemandWorks company. Both the … Read more

“smooth” package for R. Common ground. Part III. Exogenous variables. Basic stuff

One of the features of the functions in smooth package is the ability to use exogenous (aka “external”) variables. This potentially leads to the increase in the forecasting accuracy (given that you have a good estimate of the future exogenous variable). For example, in retail this can be a binary variable for promotions and we … Read more

“smooth” package for R. Common ground. Part II. Estimators

UPDATE: Starting from the v2.5.1 the cfType parameter has been renamed into loss. This post has been updated since then in order to include the more recent name. A bit about estimates of parameters Hi everyone! Today I want to tell you about parameters estimation of smooth functions. But before going into details, there are … Read more

“smooth” package for R. Common ground. Part I. Prediction intervals

UPDATE: Starting from v2.5.1 the parameter intervals has been renamed into interval for the consistency purposes with the other R functions. We have spent previous six posts discussing basics of es() function (underlying models and their implementation). Now it is time to move forward. Starting from this post we will discuss common parameters, shared by … Read more