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High dimensional and dependent functional data

Research workshop: 10-12 September 2012, Bristol, UK

Aims and objectives

The scope of this workshop is functional data analysis (FDA), with a particular focus of methodological developments and associated theoretical analysis for dependent or multi-dimensional functional data, together with applications.

Functional data analysis provides an alternative way of studying traditional data objects, recognising that it is sometimes more natural and more fruitful to view a collection of measurements as partially (and perhaps even noisily) observed realisations of random functions. The evolution of data collection technologies has only strengthened the justification for this perspective, allowing vast quantities of data to be recorded, often at a large number of finely spaced observation points.

Although much progress has been made over the last fifteen years or so, most of the existing methodologies are designed for functional data from an independent and identically distributed sample whose domain is a subset of the real line; their extension to time-dependent and higher dimensional settings is yet to be fully realised. Data of this nature arise naturally in fields as broad as neurology, space physics, finance, environmental science and orthodontics, with the term multi-dimensional referring either to multivariate functional data, or to multi-dimensionality of the domain over which the functional data object is defined.

The aim of this event is to promote discussion and transferral of ideas and methodologies between researchers working in these important areas of functional data analysis, with experts highlighting the challenges and developments in their respective fields of specialisation.

Workshop Organisers

The workshop is organised by Heather Battey (Bristol) and John Aston (Warwick), and if you have any questions, you can contact them by email using the link in the sidebar to the left.