Durham University Statistics and Probability Group
Durham University Statistics and Probability

Previous Talks 2015/2016

Wednesday 1st June 2016:

Study of Joint Type-II Censoring in Heterogeneous Populations

Speaker: Lida Fallah, Department of Mathematics, Statistics and Applied Mathematics, National University of Ireland: Galway

Abstract

Time to event, or survival, data is common in the biological and medical sciences with typical examples being time to death and time to recurrence of a tumour. In practice, survival data is typically subject to censoring with incomplete observation of some failure times due to drop-out, intermittent follow-up and finite study duration. Here, we consider the analysis of time to event data from two populations undergoing life-testing, mainly under a joint Type-II censoring scheme for heterogeneous situations. We consider a mixture model formulation and maximum likelihood estimation using the EM algorithm and conduct a simulation to study the effect of the form of censoring scheme on parameter estimation and study duration.

Wednesday 11th May 2016:

Efficient algorithms for checking consistency of probability bounds.

Speaker: Nawapon Nakharutai, Department of Mathematical Sciences, Durham University

Abstract

In situations where we have little data or where we have little expert opinion, instead of stating probabilities which can lead to an erroneous conclusion, we can specify probability bounds. Lower previsions (Walley, 1991) provide a good way to do this, by bounding expectation. In this study, we explore more efficient algorithms for checking an important basic consistency principle for lower previsions, called "avoiding sure loss". The problem of checking avoiding sure loss can be written as a fully degenerate linear program. This linear program can be solved by standard methods such as the simplex method or the affine scaling method. We propose a new way of reducing the size of this linear program and for minimal introduction of artificial variables. Since the simplex method can be extremely inefficient for fully degenerate linear programs, we explore whether there is a benefit in using other methods, such as the affine scaling method. We propose a simple way to obtain an initial interior solution for our problem, which is required for starting the affine scaling method. We also identify a condition under which the algorithm can detect inconsistency much earlier compared to standard stopping criteria from the literature. In future, we plan to investigate which method is the best suited for checking whether a lower prevision avoids sure loss. We hope that this work will encourage people to use more efficient algorithms for checking avoiding sure loss, instead of standard methods such as the simplex method which are potentially very inefficient for this specific problem.

Wednesday 27th April 2016:

Bayesian emulation and its application to analysing chemical interactions in biological plant models.

Speaker: Samuel Jackson, Department of Mathematical Sciences, Durham University

Abstract

Many processes in our world are represented in the form of complex simulator models. These models frequently take large amounts of time to run. Emulators are statistical approximations of these simulators that make predictions, along with corresponding uncertainty estimates, of what the simulator would produce. The main advantage of these emulators is the speed at which they run, which, in general, is many orders of magnitude faster than the simulators which they aim to approximate. Emulation can be used in any area of science that represents real-world systems in the form of complex models. I will provide an accessible introduction to the ideas of Bayesian emulation and history matching. I will then explain my application of Bayesian history matching by emulation in the context of biological plant models, and in particular a model of the chemical interaction network in the roots of the plant Arabidopsis. I will explain some of the practical difficulties of emulating such a complex biological model before showing some of the results I have thus far achieved. I will finally discuss briefly the idea of using these emulation techniques in the future design of actual biological experiments.

Wednesday 2nd March 2016:

Rendered invisible by official statistics: Polish workers and informal care and welfare networks in NE England.

Speaker: Lucy Szablewska, Department of Geography, Durham University

Abstract

Lucy Szablewska is carrying out qualitative research into the lived experiences of intergenerational kinship care and informal welfare networks from the perspective of transnational Polish workers and their households in NE England and Poland. One of the research aims is to shed light on broader issues - such as population aging - which are rendered largely invisible in the current debate over welfare and citizenship in the European Union. However quantitative researchers may think this sort of research is irrelevant due to the small sample size. Lucy will explain why she thinks her research is valuable, and ask how statisticians would approach the topic and measure ‘informal care’, and what the challenges of and possibilities for collaboration between quantitative and qualitative researchers in this particular field are.

Wednesday 3rd February 2016:

How different contexts influence creativity and innovation in children?

Speaker: Zarja Mursic, Department of Anthropology, Durham University

Abstract

Children are very creative but perform poorly when it comes to innovating useful tools. I study children in the contexts of a science museum to see whether different contexts influence their capabilities to innovate. I will present my first study, which tackles the question whether instructions squash creativity. In my research I am using an exhibit that is already in the museum, and also specially designed puzzle boxes and different tasks to test innovation in children. I code children’s behaviours and compare it across different conditions and contexts. At the end I might also present some plans for the future studies that are currently being designed or are in the pilot phases. All involve similar questions in relation to creativity and innovation in children.

Wednesday 20th January 2016:

Controls on the geometry of foreshore platforms: a statistical study of the North Yorkshire coast

Speaker: Zuzanna Swirad, Department of Geography, Durham University

Abstract

Foreshore platforms are semi-horizontal rock surfaces backed by coastal cliffs. Numerous studies have focused on identifying relationships between platform geometry (width, elevation and gradient) and wave intensity, rock strength and structure. However, those approximations are based on simplified models of relationships between geomorphology, geology and wave action. These therefore lack sufficient spatial resolution and coverage to enable predictive analyses of likely response of a coast to predicted changes in marine conditions (sea level and wave intensity). Here, I present a systematic study of a 4 km coastline of Staithes, North Yorkshire, based on high-resolution point cloud (ca. 100 points/m2) and ortho-photographs (pixel size ca. 0.03 m) obtained with airborne LiDAR. I represent the coast as a series of densely-spaced (25 m) and resampled (0.2 m) cross-sections normal to the coastline and link their morphometric characteristics to the spatial variability in rock properties and marine action. Statistical analysis enables the identification of key controls on platform geometry and assessment of relative roles of geological and marine factors in shaping rocky coasts.

Wednesday 16th December 2015:

Nonparametric Predictive Inference (NPI) with Copula for Bivariate Diagnostics Test Results

Speaker: Muhammad Noryanti, Department of Mathematical Sciences, Durham University

Abstract

The Receiver Operating Characteristic (ROC) curve is a common statistical tool to measure the accuracy of a diagnostic test that yields ordinal or continuous results. It is increasingly clear that in medical settings, one test result (biomarker) will not be sufficient to serve as screening device for early detection of many diseases and may be very costly. Many researchers believe that a combination of test results will potentially lead to more sensitive screening rules for detecting diseases. In this study we present a new linear combination of two test results by considering the dependence structure, by combining Nonparametric Predictive Inference (NPI) for the marginals with copulas to take dependence into account. Our method uses a discretized version of the copula which fits perfectly with the NPI method for the marginals and leads to relatively straightforward computations because there is no need to estimate the marginals and the copula simultaneously. We investigate and discuss the performance of this method by presenting results from simulation studies. The method is further illustrated via application in real data sets from the literature. We also briefly outline related challenges and opportunities for future research.

Wednesday 2nd December 2015:

Did Globalisation Exist Before the 16th Century?

Speaker: Ran Zhang, Department of Archaeology, Durham University

Abstract

It has been suggested that globalisation was gradually formed after the 16th century, while European travellers and merchants entered the Indian Ocean. However Archaeological evidence suggests that an earlier globalisation process had already been established by trades, conflicts and communications in Eurasia since the 12th and 13th centuries. To give insight into this issue, quantitative methods play an important role in understanding these historical changes. This talk aims to introduce a preliminary attempt of applying quantitative methods on archaeological topics and share some of the problems which are being faced.

Wednesday 18th November 2015:

Decision Making and Planning Under Uncertainty

Speaker: Anthony Lawson, Department of Mathematical Sciences, Durham University

Abstract

At the time investment decisions are made there may be uncertainty in many aspects which affect a decision and its outcome. Further, work with expensive simulators can make it difficult to asses how uncertainty in input affects output. An example will be presented which will consider transmission expansion planning (building new power lines) under uncertainty and how statistical emulators are a useful tool for approximating simulators and adequately considering uncertainties when making a decision.

Wednesday 4th November 2015:

Chocolate, X-Rays and Bayes Linear Methods

Speaker: Benjamin Lopez, Department of Mathematical Sciences, Durham University

Abstract

Bayes Linear Methods offer a generalisation to the Bayesian approach where the, often unrealistic, requirement for a full prior probabilistic specification is relaxed. In this talk I will discuss the foundations of Bayes linear statistical inference, taking expectation not probability to be the primitive quantity. The talk will be illustrated with 'glamorous' examples from the X-ray industry, particularly developing an on-line algorithm for detecting plastic containment in a popular brand of chocolate.

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