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The University of Southampton
The Alan Turing Institute

S3RI Seminar - Bayesian hierarchical modelling of sparse count processes with applications in retail analytics  Event

Time:
14:00 - 15:00
Date:
21 March 2019
Venue:
University of Southampton, Highfield Campus, Building 54, Room 7035.

Event details

Ioanna Manolopoulou, University College London will be delivering a seminar on 21 March at the University of Southampton. The talk will be followed by tea and cake in the staff reading room on level 4 of building 54.

In retail analytics, slow-moving-inv entory (SMI) refers to goods which rarely sell, resulting in very sparse count processes. Forecasting the sales of such goods is challenging, because traditional predictive models rely on large enough sales volumes to be accurate. In this work, we develop modelling, inferential and predictive methods able to learn the dynamics of sparse count processes for SMI products with few to no sales. We flexibly introduce covariates into the self-exciting model for sparse processes of Porter et al., (2012). We extend the model to include a cross-excitatio n contribution that allows differing series to excite one another, capturing the process of intertwined contemporaneous excitation dynamics. We integrate individual products into a Bayesian hierarchical model that accommodates shrinkage and information passing across differing sparse count process, without requiring the data for each product to exist over the same time period. We illustrate our methods on a retail analytics dataset from a major supermarket chain in the UK.

Speaker information

Ioanna Manolopoulou, Imperial College London, is an Associate Professor at the Department of Statistical Science, at University College of London, and a Turing Fellow of the Alan Turing Institute, which is the UK's national institute for Data Science. Prior to her appointment at UCL she spent 4 years at the Department of Statistical Science at Duke University as a Visiting Assistant Professor and Postdoctoral Associate working with Mike West and Sayan Mukherjee, as well as a postdoctoral fellow of the Statistical and Applied Mathematical Sciences Institute (SAMSI) as part of the Sequential Monte Carlo workshop .

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