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Department of Mathematical Sciences

Seminars

Statistics Seminars

Seminars are usually held on Monday at 14:00 in CM221, but you should check the seminar details for exceptions. Contact sunil.chhita@durham.ac.uk for more information about this seminar series.

Some statistical/probabilistic questions regarding protein structure identification

Presented by Chris Prior, University of Durham

4 June 2018 14:00 in CM221

Together with Ehmke Pohl of the Durham structural biology unit I have developed a novel technique for predicting protein structures from small angle scattering data (SAXS). SAXS is a technique where x-rays are fired at a sample of protein in solution, close to its natural environment. It is the technique with by far the most potential use, but also the hardest to interpret due to the random motion of the protein in solution. This makes the scattering data much more noisy than usual and also means a huge amount of information is lost. I will review the technique which uses a novel curve representation to fit a model to data. The potential models are drawn from a set of probability distributions which have been empirically obtained and are highly unusual. There are a series of questions concerning 1). Smoothing the noise in the experimental data which the model is fitted to. 2) Determining the shape of the parameter space of potential structures, 3) building in extra uncertainty in the model. I have reached the limit of my rudimentary knowledge in this field and need your help! I will try to get you enthused about the project in this talk.

Contact sunil.chhita@durham.ac.uk for more information

Functional Equations Involving Sibuya's Dependence Function

Presented by Nikolai Kolev, USP, Sao Paulo (IME)

18 June 2018 14:00 in CM221

We introduce a new probability aging notion via functional equation based on tail nvariance of Sibuya's dependence function specified as the ratio between the joint survival function and the product of its marginal survival functions. Solutions of the functional equation are generated by the Gumbel's type I bivariate exponential distribution and independence law. In a particular setting, we construct a version of Gumbel's law with a singular component.

Contact sunil.chhita@durham.ac.uk for more information

Presented by Alexander Holroyd, University of Washington

25 June 2018 14:00 in CM221

Contact sunil.chhita@durham.ac.uk for more information


Other seminar series

RSS North East Local Group seminars

The North Eastern Local Group of the Royal Statistical Society organises an annual programme of meetings and events allowing statisticians across the North East of England to meet and discuss topics of interest. The meetings are free to attend and non-members are always welcome. Meetings are typically held in Durham or Newcastle.

The program of these regular meetings can be found at the Royal Statistical Society North Eastern Local Group home page.

Postgraduate Seminars

These seminars offer an opportunity to find out more about what other postgraduates in the department are studying and help the speakers to improve their presentation skills in an informal atmosphere. Occasionally, postgraduate seminars are given by a member of staff. The postgraduate seminar will start in Epiphany term 2014 under the title "Stats4Grads". Postgraduates from the Statistics and Probability group, as well as from other groups and Departments, are more than welcome to attend, and to present their work with quantitative focus to a postgraduate audience.

Please see details at the Stats4Grads webpage.

Postgraduate Training Weeks

The Statistics group runs a series of postgraduate training weeks jointly organized with Newcastle University, which include lectures, seminar talks by guest speakers, computer practicals, and also seminar talks by postgraduate students. Six different training courses are offered in a 3-year-cycle, covering Multivariate Distributions (Newcastle), Smoothing (Durham), Statistical Computing (Newcastle), Foundations of Statistics (Durham), Design (Newcastle), and Modelling (Durham).