Over the year 2017 the smooth package has grown from v1.6.0 to v2.3.1. Now it is much more mature and has more downloads. It even now has its own hex (thanks to Fotios Petropoulos): A lot of changes happened in 2017, and it is hard to mention all of them, but the major ones are: […]
Conferences 2018
Next year I’m going to attend several forecasting-related conferences. I’ve decided to make a list in order not to forget what to attend. Here it is: International Symposium on Forecasting, 17-20 June, 2018, Boulder, Colorado, USA. This is the key event in forecasting, which any self-respecting forecaster should not miss. I don’t know what to […]
“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 […]
Multiplicative State-Space Models for Intermittent Time Series
John Boylan and I have been working on a paper about state-space models for intermittent data. We have had some good progress in that direction and have submitted the paper to IJF. Although it is still under review, we decided to publish the working paper in order to promote the thing. Here’s the abstract: Intermittent […]
Lecture in HSE, Saint Petersburg
Yesterday I gave a lecture to the master students of Higher School Economics, Saint Petersburg (“Marketing Analytics” programme). This was a very general lecture on “Modern Forecasting”, covering forecasting problems in practice, the solutions to these problems and modern scientific directions in the field. It seems that the lecture was well received and brought up […]
Old dog, new tricks: a modelling view of simple moving averages
Fotios Petropoulos and I have recently written a paper about a statistical model, underlying Simple Moving Average. Although we are usually taught in Forecasting courses, that there is no such thing, we found one. We have submitted this paper to International Journal of Production Research, and it has been recently accepted (took us ~4 months). […]
International Symposium on Forecasting 2017
In Cairns, Australia, I have presented the topic from Bath — One for all: forecasting intermittent and non-intermittent demand using one model. It was well received although one of the professors did not understand the main point of the presentation and I could not explain him, why this is important and why the proposed approach […]
Naughty APEs and the quest for the holy grail
Today I want to tell you a story of naughty APEs and the quest for the holy grail in forecasting. The topic has already been known for a while in academia, but is widely ignored by practitioners. APE stands for Absolute Percentage Error and is one of the simplest error measures, which is supposed to […]
smooth v2.0.0. What’s new
Good news, everyone! smooth package has recently received a major update. The version on CRAN is now v2.0.0. I thought that this is a big deal, so I decided to pause for a moment and explain what has happened, and why this new version is interesting. First of all, there is a new function, ves(), […]
“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 […]