## Archived seminars in StatisticsSeminars 1 to 50 | Next 50 seminars |

### Abdis Sattar

*Department of Population and Quantitative Health Sciences Case Western Research University USA*

Date: Tuesday 19 February 2019

### Marzia Cremona

*Penn State University*

Date: Wednesday 30 January 2019

### Geoff Jones

*Massey University*

Date: Thursday 25 October 2018

### Benoit Auvray

*Iris Data Science & Department of Mathematics and Statistics*

Date: Thursday 27 September 2018

### Matt Schofield

*Department of Mathematics and Statistics*

Date: Thursday 20 September 2018

### Alastair Lamont

*Department of Mathematics and Statistics*

Date: Thursday 13 September 2018

### Ting Wang

*Department of Mathematics and Statistics*

Date: Thursday 6 September 2018

We developed a 2D hidden Markov model to automatically analyse and forecast the spatiotemporal behaviour of tremor activity in the regions Kii and Shikoku, southwest Japan. This new automated procedure classifies the tremor source regions into distinct segments in 2D space and infers a clear hierarchical structure of tremor activity, where each region consists of several subsystems and each subsystem contains several segments. The segments can be quantitatively categorized into three different types according to their occurrence patterns: episodic, weak concentration, and background. Moreover, a significant increase in the proportion of tremor occurrence was detected in a segment in southwest Shikoku before the 2003 and 2010 long-term slow slip events in the Bungo channel. This highlights the possible correlation between tectonic tremor and slow slip events.

### Zulfi Jahufer

*AgResearch and Massey University*

Date: Thursday 23 August 2018

~~Dr Zulfi Jahufer is a senior research scientist in quantitative genetics and forage plant breeding. He also conducts the Massey University course in plant breeding. His seminar will focus on the development of novel forage grass and legume cultivars; he will also introduce the new plant breeding software tool DeltaGen.~~

### Martin Hazelton

*Massey University*

Date: Thursday 16 August 2018

In principle such sampling can be conducted using Markov chain Monte Carlo methods, through a random walk on the lattice polytope. However, it is challenging to design algorithms for doing so that are both computationally efficient and have guaranteed theoretical properties. In this talk I will describe some current work that seeks to combine methods from algebraic statistics with geometric insights in order to develop and study new polytope samplers that address these issues.

### David Bryant

*Department of Mathematics and Statistics*

Date: Thursday 9 August 2018

### Richard Norton

*Department of Mathematics and Statistics*

Date: Thursday 2 August 2018

### Zhanglong Cao

*Mathematics and Statistics Department University of Otago*

Date: Thursday 19 July 2018

### Tilman Davies

*Mathematics and Statistics Department University of Otago*

Date: Thursday 12 July 2018

### Georgia Anderson

*Oritain*

Date: Thursday 31 May 2018

Oritain measures a product's origin using 'chemical fingerprints' derived from the compositions of plants and animals. These compounds vary naturally throughout the environment. Multivariate statistical methods such as principal component analysis and linear discriminant analysis are used to extract information and determine this fingerprint from the trace element and isotopic data.

This talk will present the science used at Oritain and explore how statistics is used in a commercial environment.

### Honours and PGDip students

*Department of Mathematics and Statistics*

Date: Friday 25 May 2018

Qing Ruan : ~~Bootstrap selection in kernel density estimation with edge correction~~

Willie Huang : ~~Autoregressive hidden Markov model - an application to tremor data~~

MATHEMATICS

Tom Blennerhassett : ~~Modelling groundwater flow using Finite Elements in FEniCS~~

Peixiong Kang : ~~Numerical solution of the geodesic equation in cosmological spacetimes with acausal regions~~

Lydia Turley : ~~Modelling character evolution using the Ornstein Uhlenbeck process~~

Ben Wilks : ~~Analytic continuation of the scattering function in water waves~~

Shonaugh Wright : ~~Hilbert spaces and orthogonality~~

Jay Bhana : ~~Visualising black holes using MATLAB~~

### Hamish Spencer

*Department of Zoology*

Date: Thursday 24 May 2018

The model predicts that loci with higher levels of sexual conflict should exhibit greater differentiation between males and females in levels of dominance and that the strength of antagonistic selection experienced by one sex should be proportional to the level of dominance modification. These predictions match the recent discovery of a gene in Atlantic salmon, in which sex-dependent dominance leads to earlier maturation of males than females, a difference that is strongly favoured by selection. Finally, I suggest that empiricists should be alert to the possibility of there being numerous cases of sex-specific dominance.

### Robin Turner

*Biostatistics Unit, Dunedin School of Medicine*

Date: Thursday 17 May 2018

### Gabrielle Davie and Rebecca Lilley

*Department of Preventive and Social Medicine*

Date: Thursday 10 May 2018

### Murray Efford

*Department of Mathematics and Statistics*

Date: Thursday 3 May 2018

### Valerie Isham, NZMS 2018 Forder Lecturer

*University College London*

Date: Tuesday 24 April 2018

In this talk, I will review some stochastic point process-based models constructed in continuous time and continuous space using spatial-temporal examples from hydrology such as rainfall (where flood control is a particular application) and soil moisture. By working with continuous spaces, consistent properties can be obtained analytically at any spatial and temporal resolutions, as required for fitting and applications. I will start by covering basic model components and properties, and then go on to discuss model construction, fitting and validation, including ways to incorporate nonstationarity and climate change scenarios. I will also describe some thoughts about using similar models for wildfires.

### Valerie Isham, NZMS 2018 Forder Lecturer

*University College London*

Date: Monday 23 April 2018

Epidemic models are developed as a means of gaining understanding about the dynamics of the spread of infection (human and animal pathogens, computer viruses etc.) and of rumours and other information. This understanding can then inform control measures to limit spread, or in some cases enhance it (e.g., viral marketing). In this talk, I will give an introduction to simple generic epidemic models and their properties, the role of stochasticity and the effects of population structure (metapopulations and networks) on transmission dynamics, illustrating some past successes and outlining some future challenges.

### Alexandra Gavryushkina

*Department of Biochemistry*

Date: Monday 23 April 2018

Newly available data require developing new approaches to reconstructing dated phylogenetic trees. In this talk, I will present new methods that employ birth-death-sampling models to reconstruct dated phylogenetic trees in a Bayesian framework. These methods have been successfully applied in epidemiology and macroevolution. Dated phylogenetic histories can be informative about the past events, for example, we can learn from a reconstructed transmission tree which individuals were likely to infect other individuals. By reconstructing dated phylogenetic trees, we can also learn about the tree generating process parameters. For example, we can estimate and predict how fast epidemics spread or how fast new species arise or go extinct. In immunology, dating HIV antibody lineages can be important for vaccine design.

### David Fletcher

*Department of Mathematics and Statistics*

Date: Thursday 19 April 2018

### Andrew Anglemyer

*Naval Postgraduate School, California*

Date: Wednesday 4 April 2018

~~Dr. Andrew Anglemyer is an epidemiologist who specializes in infectious diseases and study design methodology at Naval Postgraduate School (and previously at University of California, San Francisco). Since 2009 he has been a member of the World Health Organization’s HIV Treatment Guidelines development committee and was the statistics and methods editor for the HIV/AIDS Cochrane Review Group at UC San Francisco until 2014. Dr. Anglemyer has co-authored dozens of public health and clinical peer-reviewed papers with a wide range of topics including HIV prevention and treatment in high-risk populations, firearms-related injury, paediatric encephalitis and hyponatremia. He received an MPH in Epidemiology/Biostatistics and a PhD in Epidemiology from University of California, Berkeley.~~

### Jason Gilliland

*Western University, Canada*

Date: Thursday 29 March 2018

~~Professor Jason Gilliland is Director of the Urban Development Program and Professor in the Dept of Geography, Dept of Paediatrics, School of Health Studies and Dept of Epidemiology & Biostatistics at Western University in Canada. He is also a Scientist with the Children's Health Research Institute and Lawson Health Research Institute, two of Canada's leading hospital-based research institutes. His research is primarily focused on identifying environmental influences on children’s health issues such as poor nutrition, physical inactivity, obesity, and injury. He is also Director of the Human Environments Analysis Lab (www.theheal.ca), an innovative research and training environment which specializes in community-based research and identifying interventions to inform public policy and neighbourhood design to promote the health and quality of life of children and youth.~~

### Phil Wilcox

*Department of Mathematics and Statistics*

Date: Thursday 29 March 2018

### Thomas Lumley

*University of Auckland*

Date: Thursday 22 March 2018

### Ihaka Lecture #3: Alberto Cairo

*University of Miami*

Date: Wednesday 21 March 2018

The use of graphs, charts, maps and infographics to explore data and communicate science to the public has become more and more popular. However, this rise in popularity has not been accompanied by an increasing awareness of the rules that should guide the design of these visualisations.

This talk teaches normal citizens principles to become a more critical and better informed readers of charts.

~~Alberto Cairo is the Knight Chair in Visual Journalism at the University of Miami. He’s also the director of the visualisation programme at UM’s Center for Computational Science. Cairo has been a director of infographics and multimedia at news publications in Spain (El Mundo, 2000-2005) and Brazil (Editora Globo, 2010-2012,) and a professor at the University of North Carolina-Chapel Hill. Besides teaching at UM, he works as a freelancer and consultant for companies such as Google and Microsoft. He’s the author of the books The Functional Art: An Introduction to Information Graphics and Visualization (2012) and The Truthful Art: Data, Charts, and Maps for Communication (2016).~~

[!The lectures are live-streamed;https://goo.gl/forms/ycwHTR6k8aD8Tquk1] from 6.30pm NZDST onwards on 7, 14 and 21 March 2018.

Join the local group in the Mathematics and Statistics Department for this live-stream viewing and discussion

Local contact: [Timothy.Bilton@agresearch.co.nz;Timothy.Bilton@agresearch.co.nz]

### Ihaka Lecture #2: Paul Murrell

*University of Auckland*

Date: Wednesday 14 March 2018

When combined with screen reader software, this provides information for blind and visually-impaired R users about the contents of an R plot. A minor difficulty that arises in the generation of these text descriptions involves the information about colours within a plot. As far as R is concerned, colours are described as six-digit hexadecimal strings, e.g. "#123456", but that is not very helpful for a human audience. It would be more useful to report colour names like "red" or "blue".

This talk will make a mountain out of that molehill and embark on a daring Statistical Graphics journey featuring colour spaces, high-performance computing, Te Reo, and XKCD. The only disappointment will be the ending.

~~Paul Murrell is an Associate Professor in the Department of Statistics at The University of Auckland. He is a member of the core development team for R, with primary responsibility for the graphics system.~~

[!The lectures are live-streamed;https://goo.gl/forms/ycwHTR6k8aD8Tquk1] from 6.30pm NZDST onwards on 7, 14 and 21 March 2018.

Join the local group in the Mathematics and Statistics Department for this live-stream viewing and discussion

Local contact: [Timothy.Bilton@agresearch.co.nz;Timothy.Bilton@agresearch.co.nz]

### Ihaka Lectures: A thousand words: visualising statistical data

*Live-streamed, 1st of 3 lectures*

Date: Wednesday 7 March 2018

[!The lectures are live-streamed;https://goo.gl/forms/ycwHTR6k8aD8Tquk1] from 6.30pm NZDST onwards on 7, 14 and 21 March 2018.

Local contact: [Timothy.Bilton@agresearch.co.nz;Timothy.Bilton@agresearch.co.nz]

### Alan E Gelfand

*Duke University*

Date: Tuesday 28 November 2017

The predictive process is simple to understand, routine to implement, with straightforward bias correction. It enjoys several attractive properties within the class of dimension reduction approaches and works well for datasets of order 103 or 104. It suffers several limitations including spanning only a finite dimensional subspace, over-smoothing, and underestimation of uncertainty.

So, we focus primarily on the nearest neighbor Gaussian process which draws upon earlier ideas of Vecchia and of Stein. It is a bit more complicated to grasp and implement but it is highly scalable, having been applied to datasets as large as 106. It is a well-defined spatial process providing legitimate finite dimensional Gaussian densities with sparse precision matrices. Scalability is achieved by using local information from few nearest neighbors, i.e., by using the neighbor sets in a conditional specification of the model. This is equivalent to sparse modeling of Cholesky factors of large covariance matrices. We show a multivariate spatial illustration as well as a space-time example. We also consider automating the selection of the neighbor set size.

For either specification, we embed the PGP as a dimension reduction prior and the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed. However, the future likely lies with the NNGP since it can accommodate spatial scales that preclude dimension-reducing methods.

### Matthew Parry

*Department of Mathematics and Statistics*

Date: Tuesday 24 October 2017

### Rachel Weir

*Allegheny College, Pennsylvania*

Date: Monday 16 October 2017

A common theme in the United States in recent years has been a call to increase the number of graduates in STEM (science, technology, engineering, and mathematics) fields and to enhance the scientific literacy of students in other disciplines. For example, in the 2012 report Engage to Excel, the Obama administration announced a goal of "producing, over the next decade, 1 million more college graduates in STEM fields than expected under current assumptions." Achieving these types of goals will require us to harness the potential of all students, forcing us to identify and acknowledge the barriers encountered by students from traditionally underrepresented groups. Over the past few years, I have been working to understand these barriers to success, particularly in mathematics. In this talk, I will share what I have learned so far and how it has influenced my teaching.

### David Fletcher

*Department of Mathematics and Statistics*

Date: Thursday 12 October 2017

### Honours and PGDip students

*Department of Mathematics and Statistics*

Date: Friday 6 October 2017

Jodie Buckby : ~~Model checking for hidden Markov models~~

Jie Kang : ~~Model averaging for renewal process~~

Yu Yang : ~~Robustness of temperature reconstruction for the past 500 years~~

MATHEMATICS

Sam Bremer : ~~An effective model for particle distribution in waterways~~

Joshua Mills : ~~Hyperbolic equations and finite difference schemes~~

### Ken Ono

*Emory University; 2017 NZMS/AMS Maclaurin Lecturer*

Date: Thursday 5 October 2017

Ramanujan’s work has had a truly transformative effect on modern mathematics, and continues to do so as we understand further lines from his letters and notebooks. In this lecture, some of the studies of Ramanujan that are most accessible to the general public will be presented and how Ramanujan’s findings fundamentally changed modern mathematics, and also influenced the lecturer’s work, will be discussed. The speaker is an Associate Producer of the film ~~The Man Who Knew Infinity~~ (starring Dev Patel and Jeremy Irons) about Ramanujan. He will share several clips from the film in the lecture.

Biography: Ken Ono is the Asa Griggs Candler Professor of Mathematics at Emory University. He is considered to be an expert in the theory of integer partitions and modular forms. He has been invited to speak to audiences all over North America, Asia and Europe. His contributions include several monographs and over 150 research and popular articles in number theory, combinatorics and algebra. He received his Ph.D. from UCLA and has received many awards for his research in number theory, including a Guggenheim Fellowship, a Packard Fellowship and a Sloan Fellowship. He was awarded a Presidential Early Career Award for Science and Engineering (PECASE) by Bill Clinton in 2000 and he was named the National Science Foundation’s Distinguished Teaching Scholar in 2005. In addition to being a thesis advisor and postdoctoral mentor, he has also mentored dozens of undergraduates and high school students. He serves as Editor-in-Chief for several journals and is an editor of The Ramanujan Journal. He is also a member of the US National Committee for Mathematics at the National Academy of Science.

### Katie Jones and Olya Shatova

*Oritain Dunedin*

Date: Monday 2 October 2017

##Note day, time and venue##

Oritain Global Ltd is a scientific traceability company that verifies the origin of food, fibre, and pharmaceutical product by combining trace element and isotope chemistry with statistics. Born in the research labs at the Chemistry Department in the University of Otago, Oritain has grown to become a multinational company with offices in Dunedin, London, and Sydney, and with clients from around the globe. Dr Katie Jones and Dr Olya Shatova are Otago alumni working as scientists at Oritain Dunedin. They will provide an overview of the science behind Oritain and discuss their transition from academic research to commercialized science.

### Mike and Sue Carson

*Carson Associates Ltd*

Date: Thursday 28 September 2017

### Mik Black

*Department of Biochemistry*

Date: Thursday 21 September 2017

### Timothy Bilton

*Department of Mathematics and Statistics*

Date: Thursday 14 September 2017

### Martin Hazelton

*Massey University*

Date: Thursday 7 September 2017

In this talk I will discuss network tomography for a rather general class of traffic models. I will describe some recent progress on model identifiability. I will then discuss the development of effective MCMC samplers for simulation-based inference, based on insight provided by an examination of the geometry of the space of feasible route flows.

### Lech Szymanski

*Department of Computer Science*

Date: Thursday 31 August 2017

### John Holmes

*Department of Mathematics and Statistics*

Date: Thursday 24 August 2017

### Moana Theodore

*Department of Psychology*

Date: Thursday 17 August 2017

### Matthew Schofield

*Department of Mathematics and Statistics*

Date: Thursday 10 August 2017

### Phil Wilcox

*Department of Mathematics and Statistics*

Date: Thursday 3 August 2017

### Peter Dillingham

*Department of Mathematics and Statistics*

Date: Thursday 27 July 2017

### Alastair Lamont

*Department of Mathematics and Statistics*

Date: Thursday 20 July 2017

### Michael Lee

*Department of Mathematics and Statistics*

Date: Thursday 13 July 2017

### Jim Cotter

*School of Physical Education, Sport and Exercise Sciences*

Date: Thursday 1 June 2017