## Operational Research and Statistics Seminars 2013-2014

### Programme

All seminars will commence at 12:10pm in room M/2.06, The Mathematics Building, Cardiff University, Senghennydd Road (unless otherwise stated).

Please contact Dr Iskander Aliev for more details regarding Operational Research/WIMCS lectures and Dr Jonathan Gillard for more details regarding Statistics lectures.

##### 9 October 2013

**Speaker: **Dr Mark Kelbert (Swansea University).

**Title:** Earthquake forecasting: Statistics and Information.

**Abstract:** We present an axiomatic approach to the earthquake forecasting in terms of multi-component random fields on the lattice. This approach provides a method for constructing point estimates and confidence intervals for conditional probabilities of strong earthquakes under conditions on the levels of precursors. Also, it provides an approach for setting multilevel alarm system and hypothesis testing for binary alarms. We propose a method of comparison for different earthquake forecasts in terms of the increase of Shannon information. 'Forecasting' and 'prediction' of earthquakes are equivalent in this approach.

##### 23 October 2013

**Speaker: **Prof. Anatoly Zhigljavsky (Cardiff University).

**Title:** Stochastic methods in multiobjective optimization.

**Abstract:** TBC.

##### 30 October 2013

**Speaker: **Dr Andreas Artemiou (Cardiff University).

**Title:** Dimension Reduction in Regression.

**Abstract:** Firstly I will go through a historical overview of how dimension reduction is achieved in regression problems (with a focus on linear regression). I will be spending more time explaining why unsupervised methods like Principal Component Analysis will not work and I will be sufficient dimension reduction, a class of supervised dimension reduction techniques, that have been developed the last 25 years. After the general introduction (and probably in a second talk) I will focus on the use of machine learning algorithm and more specifically the use of Support Vector Machine to achieve linear and nonlinear dimension reduction in a unified framework. I will discuss the advantages of this type of methodology over previous methods, as well as ways to improve the shortcomings of it, (by the end of it, I will discuss in detail current research I am doing on this topic).

##### 13 November 2013 at 12:10

**Speaker: **Dr Andreas Artemiou (Cardiff University).

**Title:** Using support vector machines in sufficient dimension reduction.

**Abstract:** Having introduced the general framework for sufficient dimension reduction in the first part of the talk, in this part I will discuss how Support Vector Machine can be used to achieve both linear and nonlinear sufficient dimension reduction under a unified framework (idea discussed in Li, Artemiou and Li (2011)). Then I will discuss possible problems of the algorithms as well as possible solutions we are currently working on.

##### 27 November 2013

**Speaker: **Gareth Davies (Cardiff University).

**Title:** Calibration in Survey Sampling.

**Abstract:** Calibration is a technique frequently used in sample surveys. It consists of determining a set of final estimation weights that satisfy some benchmark constraints and that are as close as possible to a set of initial design weights. The motivation for the calibration problem and the main reasons for calibration in practice are introduced.
In this talk, we consider various methods of calibration. When constraints are 'hard' it is not guaranteed that the weights will remain positive or 'close' to the initial design weights. A variety of distance functions are considered and their relative merits explored. The chi-square distance function receives most attention in calibration literature, but is this the most appropriate function? Alternative calibration approaches will be introduced, namely empirical likelihood calibration, soft calibration and model calibration.

##### 15 January 2014

**Speaker: **Dr David Hodge (University of Nottingham).

**Title:** Restless bandits for resource allocation.

**Abstract:** I will give an overview of restless bandit theory and talk about some applications. Areas of application may involve queues, stock control and machine maintenance and all concern the dynamic sequential allocation of divisible resources between `competing' projects/bandits. I will discuss some problems where bandit `indices' can yield excellent scalable heuristics for high dimensional resource allocation problems. I will also try to discuss some work on asymptotic optimality with a view to highlighting the many areas where the result could be of use. The talk will attempt to provide an overview to a number of papers of work in this area with authors including K. Glazebrook, C. Kirkbride (both at Lancaster), and J. Minty.

##### 19 February 2014

**Speaker: **Dr Felix Fischer (Cambridge).

**Title:** Optimal Impartial Selection.

**Abstract:** We study the problem of selecting a member of a set of agents based on impartial nominations by agents from that set. The problem was studied previously by Alon et al. and by Holzman and Moulin and has important applications in situations where representatives are selected from within a group or where publishing or funding decisions are made based on a process of peer review. Our main result concerns a randomized mechanism that in expectation selects an agent with at least half the maximum number of nominations. Subject to impartiality, this is best possible. (joint work with Max Klimm).

##### 26 March 2014

**Speaker: **Danijel Grahovac (University of Osijek).

**Title:** Asymptotic properties of the partition function and applications.

**Abstract:** The so-called partition function is a sample moment statistic based on blocks of data and it is often usedin the context of multifractal processes. It will be shown that its behavior is strongly influenced by the tailof the distribution underlying the data both in i.i.d. and weakly dependent cases. As a fi rst applicationof this result, graphical and estimation methods for the tail index are developed. Proposed methods aretested against some well-known estimators on simulated and real world data. Second application involvesdetermining scaling properties of stochastic processes. It is shown that scaling functions method is unreliableand may produce spurious multifractality in the presence of heavy tails.