One of the features of functions of smooth package is the ability to work with intermittent data and the data with periodically occurring zeroes. Intermittent time series is a series that has non-zero values occurring at irregular frequency (Svetuknov and Boylan, 2017). Imagine retailer who sells green lipsticks. The demand on such a product will […]

# intermittent demand

# International Symposium on Forecasting 2018

This year I have presented an extension of the research from ISF2017, called “Forecasting intermittent data with complex patterns”. This time we developed the model with “logistic probability”, which allows capturing complex patterns in demand occurrence part of the data. I also tried making the presentation more entertaining and easier to understand by a wider […]

# 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 […]

# Seminar and presentation at Bath University

Last week I have visited Bath University, where Dr. Fotios Petropoulos works. He organised a scientific seminar, where I could present my recent research on topic “One for all: forecasting intermittent and non-intermittent demand using one model“. The presentation was well received and rose several interesting questions from the participants of the seminar, which will […]

# 19th IIF Workshop presentation

An IIF workshop “Supply Chain Forecasting for Operations” took place at Lancaster University on 28th and 29th of June. I have given a presentation on a topic that John Boylan and I are currently working on. We suggest a universal statistical model, that allows uniting standard methods of forecasting (for example, for fast moving products) […]