[Forum SIS] seminars of Tom Fearn and Mark Girolami

[Irene Poli]

European Centre for Living Technology (ECLT, www.ecltech.org),  University Ca' Foscari Venice

Statistics Seminars



       1.  Friday 18th March at 11.00 am,  in the Conference Room of Ca' Minich 


                                                                                            Prof. Tom Fearn

                                                                   Department of Statistical Science

                                                                                          University College London

                                            Chemometrics and Calibration in Near Infrared Spectroscopy


   Abstract:   

Quantitative near infrared spectroscopy (NIR) has made extensive use of high-dimensional data since the early 1980's, and this application has been closely associated with the development of so-called chemometric methods such as partial least squares. The talk will describe some of the methodology used for NIR calibration, highlighting both successes and pitfalls.
........................................................................


     2.  Monday 21st March at 11.00 am,  in the Conference Room of Ca' Minich 


                                                                                            Prof. Mark Girolami

                                                                        Department of Statistical Science

                                                                                              University College London                                                                                   

                                            Efficient Sampling from High-Dimensional Distributions : MCMC on Riemann Manifolds


   Abstract: The requirement to sample efficiently from high-dimensional densities arises in a vast number of application areas in statistics - ranging from spatial statistics to clinical proteomics. The challenges which have to be met include complex correlation structure as well as near degenerate densities along dimensions. A recent development in Markov Chain Monte Carlo (MCMC) methodology appears to address a number of these issues in a systematic manner where the underlying geometric structure of statistical models is exploited in the design of transition operators for MCMC. This talk will provide a tutorial introduction to MCMC on Riemann manifolds and then study a range of high-dimensional problems considering the strengths and weaknesses of this methodology for High-D sampling.



_______________________________________________
Statistics Seminars at ECLT are jointly organised by  Irene Poli and Phil Brown.
Further information on the seminars are available at www.ecltech.org

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://www.stat.unipg.it/pipermail/sis/attachments/20110314/52d38367/attachment-0001.html>