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Canberra Branch -- Dennis Trewin prize 2022

When
25 Oct 2022
5:15 PM - 7:15 PM
Location
Hybrid (in-person and on Zoom)

SSA Canberra invites you to the 2022 Dennis Trewin prize! The Dennis Trewin Prize, named after the former Australian Statistician Dennis Trewin AO, is awarded annually by the Canberra Branch for outstanding research in statistics or data science by a current or recently graduated postgraduate student from a ACT or regional NSW (excluding Sydney-Newcastle-Wollongong) university.

This year we have changed the method of evaluation of candidates for the Dennis Trewin Prize. We have formed a short-list of three candidates to each present their work and be judged on the day. Each candidate will have 20-25 minutes for their presentation and 5 minutes for audience questions. In partnership with the Australian Bureau of Statistics, monetary prizes totalling $1,000 or more will be on offer and distributed at the discretion of the selection panel.

After the presentations the panel will be given time to deliberate in a zoom breakout room, while those attending in-person will be asked to move outside and will have the opportunity to mingle with the candidates. After judging has been completed, all will be invited back in after which the winners and runners-up will be announced.

We will be having an SSA Canberra dinner that evening at a nearby venue, so if you are interested in attending the dinner and catching up with members and friends in person, please see below for details for RSVP-ing.

Times (+/- some standard errors): 5:15pm – 7:15pm AEDT

Venue: Room 5.02 in Marie Reay Teaching Centre, The Australian National University, or via Zoom. For in-person attendance, please RSVP by 4pm Monday 24th October by entering your details on the SSA Canberra meeting and dinner attendance sheet, or contacting warren.muller@csiro.au. For in-person attendance, MASKS MUST BE WORN. No food or drink is allowed in the venue.

Zoom link: https://anu.zoom.us/j/88180229928?pwd=N2ZhNXd1ZkZoOS9VV2dwUURqTUR4Zz09. The zoom link will be open from 5.00pm. RSVP is not required. Full zoom details given at the end of the email.

Speakers

1: Fui Swen Kuh: A holistic Bayesian framework for modelling socio-economic health

2: Zhi Yang Tho: Joint Mean and Correlation Regression Modelling for Multivariate Data

3: Jiazhen Xu Generalized Score Matching for Regression

Full details are provided below.

Dinner: After the talks we will be holding a dinner at Badger & Co in the adjoining building at ANU (Badger & Co – Uni Pub – ANU – Canberra (badgerandco.com.au) at 7.30pm. If you are interested in attending the dinner, please let me know by 4pm Monday 24 October by entering your details at SSA Canberra meeting and dinner attendance sheet, or contacting me (warren.muller@csiro.au; 0407 916 868). Please regard this as a firm commitment, not just an intention. For withdrawals after the deadline, please remove your name from the sheet and phone or text me (0407 916 868).

NOTE: We are offering discounts to SSA early career and student members who attend dinner! For this meeting, dinners will be a fixed charge of $5 for student members and $10 for early career members. As the venue is card payment only, subsidised participants should pay cash to Warren Muller, who will pay for their meal by card. Other participants should purchase their own meals. Drinks will be paid for by SSA through Warren Muller.

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Speaker #1: Fui Swen Kuh: A holistic Bayesian framework for modelling socio-economic health

Abstract

In our work, we propose the novel LAtent Causal Socioeconomic Health (LACSH) index to holistically evaluate a country’s performance from the social, economic, political and environmental aspects to replace the narrowly focused gross domestic product (GDP). Our framework integrates the latent health factor index (LHFI) structure (a latent factor model), spatial modelling to formally account for spatial dependency among the nations and causal modelling to evaluate the impact of a continuous policy variable. We apply our methodology to investigate the causal effect of mandatory maternity leave days and government expenditure on healthcare on a country’s health. We believe this comprehensive approach is the first in the literature to capture a country’s holistic performance while accounting for spatial effects and examining the causal effect of public policy.

Biography

Swen is currently a Research Fellow in Statistics at Monash University working in collaboration with Columbia University in the United States. She recently completed her PhD in Statistics at ANU in 2022. Her research areas include hierarchical modelling, Bayesian methods and inference, and applications to social science.

Speaker #2: Zhi Yang Tho: Joint Mean and Correlation Regression Modelling for Multivariate Data

Abstract

In the analysis of multivariate or multi-response data, researchers are often not only interested in studying how the mean (say) of each response evolves as a function of covariates, but also and simultaneously how the correlations between responses are related to one or more similarity/distance measures. To address such research questions, we propose a novel joint mean and correlation regression model that simultaneously regresses the mean of each response against a set of covariates and the correlations between responses against a set of similarity measures, which can be applied to a wide variety of correlated discrete and (semi-)continuous responses. Under a general setting where the number of responses can tend to infinity with the number of clusters, we demonstrate that our proposed joint estimators of the regression coefficients and correlation parameters are consistent and asymptotically normally distributed with differing rates of convergence. We apply the proposed model to a dataset of overdispersed counts of 38 Carabidae ground beetle species sampled throughout Scotland, with results showing in particular that beetle total length and breeding season have statistically important effects in driving the correlations between beetle species.

Biography

Zhi Yang is a PhD in Statistics student at the Australian National University. His research interests lie in joint mean-covariance modelling, multivariate analysis, spatial statistics and robust statistics.

Speaker #3: Jiazhen Xu: Generalized Score Matching for Regression

Abstract

Many probabilistic models that have an intractable normalizing constant may be extended to contain covariates. Since the evaluation of the exact likelihood is difficult or even impossible for these models, we propose a novel generalized score matching method to avoid explicit computation of the normalizing constant.

Biography

I am a second-year doctoral student in Statistics at the Australian National University under the supervision of Professor Andrew Wood, Associate Professor Janice Scealy and Dr. Tao Zou. My research interests lie in non-Euclidean data analysis, robust statistics, and estimation methods for intractable likelihood.

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Full Zoom link:

Topic: Dennis Trewin Prize Event

Time: Oct 25, 2022 05:00 PM Canberra, Melbourne, Sydney

Join Zoom Meeting: https://anu.zoom.us/j/88180229928?pwd=N2ZhNXd1ZkZoOS9VV2dwUURqTUR4Zz09

Meeting ID: 881 8022 9928

Password: 058184

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