Department of Statistics


Dictionary learning
Prof. Bogdan Dumitrescu

Speaker: Prof. Bogdan Dumitrescu

Affiliation: University Politehnica of Bucharest

When: Wednesday, 1 March 2017, 11:00 am to 12:00 pm

Where: 303S-561 : Room 561, Level 5, Uni building 303 South wing, The University of Auckland at 38 Princes Street, Auckland CBD

Sparse representations have seen a huge development in the latest 20 years, due to their ability to capture parsimoniously the features of a signal. The overcomplete basis used for sparse representations, called also dictionary, can be fixed or adapted to the class of signals at hand. The presentation focuses on the latter case and the associated problem of training the dictionary. There are several classes of methods, based on different ideas, all of them simplifications of the underlying optimization problem, which is NP-hard. The huge number of variables is also a basic difficulty. Besides the standard problem of dictionary learning, some modifications suited for classification will be presented, because classification is one of the applications with significant results. Other variations of the problem include regularization and adaptations to incoherent and structured dictionaries.

Further details:

How to assign partial credit on an exam of true-false questions?

Speaker: Jing Liu (Stephen), PhD

Affiliation: Shanghai Jiao Tong University, China

When: Wednesday, 21 December 2016, 1:00 pm to 2:00 pm

Where: 303-G14

True-false questions are adaptable to the measurement of a wide variety of learning outcomes. It is particularly popular in statistics. In contrast to some other disciplines of knowledge, many questions in statistics do have a single and objective correct answer, with all other answers being agreed upon as being incorrect. So students in statistics classes can be examined in an objective manner using true-false questions effciently. However, it is known to have its limitations. Perhaps the most obvious problem is the zero-tolerance approach to mistakes, which can distort the relationship between aptitude and credit. Secondly, it does not provide diagnostic information. Lastly, it is susceptible to cheating. This talk looks at how to mathematically alleviate those issues while retaining the advantages of using true-false questions in statistics.

The SaFE Project: Developing an intervention to promote safe sex and healthy relationships among further education students in the UK.
 Dr Honor Young

Speaker: Dr Honor Young

Affiliation: Lecturer in Quantitative Research Methods, Cardiff University

When: Thursday, 15 December 2016, 11:00 am to 12:00 pm

Where: 303-B07

The promotion of safe and healthy sexual behaviour and relationships is key to young people

Measuring poverty in the European Union
Dr Marco Pomati

Speaker: Dr Marco Pomati

Affiliation: Lecturer in Quantitative Sociology

When: Thursday, 15 December 2016, 11:00 am to 12:00 pm

Where: 303-B07

Dr Marco Pomati will outline his survey-based research on the measurement of material deprivation funded by EUROSTAT and how people cope with poverty in the UK and Europe. He will also outline his plans for research on the measurement of living standards starting in January 2017 and funded by the Nuffield Foundation. He will also summarise some lessons from his newly-designed Undergraduate course Knowing the Social World: Online and Offline Surveys run between September and December 2016 for the first time as part of the BSc Social Analytics.

User Equilibria in Systems of Processor Sharing queues: 2016 ORSNZ conference presentation, extended cut

Speaker: Niffe Hermansson

Affiliation: University of Auckland

When: Wednesday, 14 December 2016, 10:00 am to 11:00 am

Where: 303-G14

This talk will be an extended version of my talk at the NZSA/ORSNZ Conference, so if you are interested and missed it there, now is your chance.

We consider the behaviour of selfish users in systems of parallel queues operating under processor sharing. Previous work has shown that these systems exhibit interesting, and sometimes perplexing, behaviours. In this presentation we will see some examples of surprising system behaviour, but also some encouraging properties of the system at equilibrium.

Is more statistics good for everyone? Cardiff Q-Step FE/Schools Initiative

Speaker: Rhys Jones, Lecturer in Quantitative Methods, Further Education and Admissions Tutor

Affiliation: Cardiff University

When: Tuesday, 13 December 2016, 11:00 am to 12:00 pm

Where: 303-B07

There has been an overwhelmingly positive response to the Further Education (FE)/School engagement work, linked to developing and promoting context rich statistical courses, across England and Wales. These courses, primarily aimed at year 12 and 13 students, are focussed on the development of a new subject area called Social Analytics (the scientific investigation of social processes using statistical techniques and analysis). Individuals attending this session will gain practical insights into the innovative partnerships developed between universities, exam boards and schools/ FE colleges. An exemplification of the collaborative benefits will also be explored. The session will also focus on the pedagogical basis of the qualifications being created, the interdisciplinary nature and skills centred approach that has been adopted, and the educational impacts in terms of student attainment and achievement in other subject areas. The case will be made that developing students critical thinking and conceptual understanding of statistics, can have positive impacts on many other subject areas. These positive impacts include attitudes towards mathematics and statistics, as well as educational achievement.

To Fuel or Not to Fuel? Is that the Question?
Javier Cano, Professor

Speaker: Javier Cano, Professor

Affiliation: Rey Juan Carlos University in Madrid, Spain

When: Wednesday, 7 December 2016, 11:00 am to 12:00 pm

Where: 303-412

According to the International Air Transport Association, the industry fuel bill accounts for more than 25% of the annual airline operating costs. In times of severe economic constraints and increasing fuel costs, air carriers are looking for ways to reduce costs and improve fuel efficiency without putting flight safety into jeopardy. In particular, this is inducing discussions on how much additional fuel to put in a planned route to avoid diverting to an alternate airport due to Air Traffic Flow Management delays. We provide here a general model to support such decisions. We illustrate it with a case study and provide comparison with the current practice, showing the relevance of our approach.

Publish for Pleasure: Embracing modern tools for research publications
Paul Murrel

Speaker: Paul Murrel

Affiliation: Department of Statistics, University of Auckland

When: Tuesday, 15 November 2016, 11:00 am to 12:00 pm

Where: 303-B07

This talk will describe some of the workflows and tools that I use to create research publications and I will attempt to explain why these tools are so groovy. The focus will be on tools that improve efficiency (e.g., XML and literate documents), tools that optimize accessibility (e.g., Creative Commons and DIY publishing), and tools that promote reproducibility (e.g., Docker).

Polytope Samplers for Network Tomography
Martin Hazelton

Speaker: Martin Hazelton

Affiliation: Statistics and Bioinformatics Group, Massey U.

When: Wednesday, 12 October 2016, 11:00 am to 12:00 pm

Where: Room 303-310

Volume network tomography is concerned with inference about traffic flow characteristics based on traffic measurements at fixed locations on the network. The quintessential example is estimation of the traffic volume between any pair of origin and destination nodes using traffic counts obtained from a subset of the links of the network. The data provide only indirect information about the target variables, generating a challenging type of statistical linear inverse problem.

Given the observed traffic count, the latent route traffic volumes are constrained to lie in an integer convex polytope (the solution space for an underdetermined linear system with non-negativity constraints). Implementation of inference using MCMC or stochastic EM algorithms requires that we sample from this (high dimensional) polytope. In this talk I will describe some recent progress on developing efficient polytope samplers, and will outline links to related problems such as resampling entries in contingency tables conditional on various marginal totals.

Hypothesis tests based on large quadratic forms
Thomas Lumley

Speaker: Thomas Lumley

Affiliation: Dept. Statistics, U. Auckland

When: Wednesday, 5 October 2016, 11:00 am to 12:00 pm

Where: Room 303S-561

When a set of n component tests is combined using a weight matrix other than the inverse of their covariance matrix, the natural large-sample approximation to the distribution is a quadratic form in Gaussian variables. There are three classes of existing ways to evaluate tail probabilities for this distribution: approximations based on matching moments, a saddlepoint approximation, and essentially exact methods based on infinite series. For many purposes all of these are satisfactory. However, when extreme tail probabilities are required, as in DNA resequencing studies, all the existing methods that are sufficiently accurate take n^3 time. With modern DNA resequencing projects reaching 10,000 participants and interest in tests combining as many as 10,000-100,000 variants, these methods are prohibitively slow. I will present a new approximation based on a low-rank approximate SVD, and explain why it is both fast and accurate.

Spatial Modelling with Template Model Builder: Applications to multivariate methods in ecology
Andrea Havron

Speaker: Andrea Havron

Affiliation: Dept. Statistics, U. Auckland

When: Thursday, 22 September 2016, 3:00 pm to 4:00 pm

Where: Room 303-310

[Please note the unusual day and time.]

Recent and often rapid changes in environmental states as a result of human impact have led to calls for improved predictive and inferential capabilities in ecological modelling. Due to the complexity of ecological systems and the tendency of observations from these systems to violate assumptions of independence, new methodologies are warranted to better incorporate spatial autocorrelation into model design. Template Model Builder (TMB), an automated differential modelling environment, allows spatial structure to be modelled as spatial random effects within a full likelihood-based framework. The sparse precision matrix, Q, is estimated by a Gaussian Markov Random Field using a Stochastic Partial Differentiation Equation, which has a Gaussian Field with Matern covariance function as its solution. By performing optimization procedures with a sparse Q, the computational burden of estimating the spatial random effects is improved from O(n3) to O(n3/2). Through this application, more complex ecological processes may be analysed.

In this talk, I will review new spatial modelling methods in R-INLA and TMB to estimate the Gaussian Markov Random Field. I will then discuss multivariate applications of these methods to issues in fisheries management, such as predicting joint species distributions from biomass data and predicting fisheries bycatch hotspots. I will also introduce the development of a new method for estimating community ecology's beta diversity.


Please give us your feedback or ask us a question

This message is...

My feedback or question is...

My email address is...

(Only if you need a reply)

A to Z Directory | Site map | Accessibility | Copyright | Privacy | Disclaimer | Feedback on this page