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Analysis of reduction of complexity

The analysis of many statistical problems is complicated by the fact that data often lies in a high-dimensional space. This increases the uncertainty associated with many algorithms, and is often referred to as `the curse of dimensionality'. Many authors use the method of Principal Components to find a simpler version of the problem, while capturing the essential variation that exists. Recently, Dennis Cook has proposed the related Principal Fitted Components (PFC) algorithm, which works in a similar way, but takes more advantage of the data. Oliver Johnson has published a paper analysing the performance of Cook's algorithm, and explaining some of the simulation results he gives. Johnson gives conditions under which PFC will perform well, and shows that in certain situations it will outperform the more standard Principal Components algorithm. Read more...

Brunel Postdoctoral Fellowships in Statistics (2 posts)

Applications are invited for two Brunel Postdoctoral Fellowships in Statistics, tenable from 1 August 2012 (or a date to be agreed) until 3 July 2014. The fellowship is part of a multi-million pound grant aimed at supporting an ambitious research programme to support "Statistics underpinning Science, Technology and Industry" (SuSTaIn).

You will be expected to undertake a programme of self-directed research in any branch of Statistics as part of a Statistics Group with an outstanding international reputation for research. The School of Mathematics is one of the leading centres for research and teaching in mathematical sciences in the UK, and offers a stimulating and friendly environment with first-rate facilities.

Contract: Fixed Term Contract (two years) Salary: £33,884 - £38,140 p.a.

Grade: Level b in Pathway 2.

Closing date for applications: 9:00am 01 Jun 2012.

Interviews are expected to be held during late June 2012.

For further information on the fellowships and application process, click here.