BEGIN:VCALENDAR
VERSION:2.0
PRODID:Ludger using PHP/v0.1
X-PUBLISHED-TTL:PT15MIN
METHOD:PUBLISH
X-WR-CALNAME:Maths & Stats: Statistics Seminar
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10945@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230113T150000Z
DTEND:20230113T160000Z
SUMMARY:Statistics Seminar: Prior Dependence in L1-regularized Bayesian Regression - Christopher Hans (Department of Statistics\, Ohio State University)
DESCRIPTION:Abstract: The regularization of regression coefficients has become a central component of research in the statistical sciences due to its importance in applied data analysis in many other fields of science. From a Bayesian perspective\, regularization is imposed...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10945
LOCATION:Zoom
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10912@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230120T150000Z
DTEND:20230120T160000Z
SUMMARY:Statistics Seminar: Estimating the limiting shape of bivariate scaled sample clouds for self-consistent inference of extremal dependence properties - Emma Simpson (University College London)
DESCRIPTION:Abstract: An integral part of carrying out statistical analysis for bivariate extreme events is characterising the tail dependence relationship between the two variables. For instance\, we may be interested in identifying the presence of asymptotic dependence and/or in determining whether an individual variable can be large while the other is of...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10912
LOCATION:Zoom
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11014@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230201T140000Z
DTEND:20230201T150000Z
SUMMARY:Applied Mathematics\, SofTMech\, Statistics Seminar: Inference in cardiac mechanics - Dirk Husmeier (University of Glasgow)
DESCRIPTION:Abstract: I will be giving a brief overview of the work on inference in cardiac mechanics at SofTMech\, including the following topics: - Simulation versus emulation of cardiac mechanics- Forward versus inverse uncertainty quantification- Structural versus practical identifiability- Dimension reduction of the left...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11014
LOCATION:CTT BOYD ORR:709AB
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10948@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230217T150000Z
DTEND:20230217T160000Z
SUMMARY:Statistics Seminar: Distilling importance sampling for likelihood-free inference - Dennis Prangle (University of Bristol)
DESCRIPTION:Abstract: Likelihood-free inference involves inferring parameter values given observed data and a simulator model. The simulator is computer code taking the parameters\, performing stochastic calculations\, and outputting simulated data. In this work\, we view the simulator as a function whose inputs are (1) the parameters and (2) a vector of pseudo-random...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10948
LOCATION:Zoom
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11031@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230310T150000Z
DTEND:20230310T160000Z
SUMMARY:Statistics Seminar: Transferable species distribution modelling: Comparative performance evaluation and interpretation of novel Generalized Functional Response models - Shaykhah Aldossari (University of Glasgow)
DESCRIPTION:Abstract: Predictive species distribution models (SDMs) are becoming increasingly important in ecology\, in the light of rapid environmental change. The predictions of most current SDMs are specific to the habitat composition of the environments in which such models were fitted. However\, species respond...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11031
LOCATION:Boyd Orr 709A
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11036@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230320T130000Z
DTEND:20230320T140000Z
SUMMARY:Statistics Seminar: A useful parametric specification to model epidemiological data - Marco Mingione (Roma Tre University)
DESCRIPTION:Abstract: Recent epidemic outbreaks reignited the debate on how to properly model epidemiological indicators in order to (i) gain insights into the dynamics of infectious diseases\, (ii) generate epidemic forecasts and (iii) implement timely prevention policies. We argue that the five-parameter specification of the Richards' curve\, often used in the context of...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11036
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10925@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230324T150000Z
DTEND:20230324T160000Z
SUMMARY:Statistics Seminar: Binscatter and adaptive decision tree - Matias D. Cattaneo (Princeton University\, USA)
DESCRIPTION:Abstract: Part 1 Binned scatter plots\, or binscatters\, have become a popular and convenient tool in applied microeconomics for visualizing bivariate relations and conducting informal specification testing. However\, a binscatter\, on its own\, is very limited in what it can characterize about the conditional mean. We introduce a suite of formal...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10925
LOCATION:JOSEPH BLACK:C407 AGRICULT
SEQUENCE:5
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11013@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230421T140000Z
DTEND:20230421T150000Z
SUMMARY:Statistics Seminar: Regression markets and energy forecasting applications - Pierre Pinson (Imperial College London)
DESCRIPTION:Abstract: The operation of energy systems heavily relies on data\, where most agents would benefit from also accommodating data (or more generally information) for other agents. There does not exist\, however\, a general framework that would allow incentivizing information sharing\, with the general objective of improving energy system operation in a...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11013
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10960@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230425T120000Z
DTEND:20230425T130000Z
SUMMARY:Statistics Seminar: BioSS Showcase - Peatland Plants and Crop Variety Trials - Mark Brewer\, Claire Harris and Tess Vernon (BioSS)
DESCRIPTION:Abstract: What is BioSS? Mark will briefly answer this question before giving way to two colleagues who will talk about their recent work\, using advanced statistical and biomathematical method to solve important biological and environmental problems. Claire Harris - Modelling peatland plant life Peatlands are hugely important ecosystems in the UK\,...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10960
LOCATION:Maths 311B
SEQUENCE:5
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11015@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230505T140000Z
DTEND:20230505T150000Z
SUMMARY:Statistics Seminar: Assessing the empirical relationship between agriculture\, manure and ammonia in the Po Valley\, Italy - Paolo Maranzano (University of Milano Bicocca)
DESCRIPTION:Abstract: Ammonia () is a crucial contributor to air pollution levels\, as it can become particulate matter after combining with other pollutant materials from various sources. Around 75% of European ammonia emissions come from livestock production. Emissions occur at all stages of...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11015
LOCATION:Maths 311B
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11049@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230530T120000Z
DTEND:20230530T130000Z
SUMMARY:Statistics Seminar: There is No Free Variable Importance: Statistical Issues in Explainable Machine Learning - Giles Hooker (Cornell University)
DESCRIPTION:Abstract: The field of machine learning — loosely defined as nonparametric statistical modeling — has become enormously successful over the past fifty years\, partly by forgoing the parametric models familiar to statisticians. A consequence of this philosophy has been that these methods result in algebraically-complex models that...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11049
LOCATION:Maths 311B/Zoom
SEQUENCE:5
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11054@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230616T140000Z
DTEND:20230616T150000Z
SUMMARY:Statistics Seminar: Copula-based approaches for analyzing non-Gaussian spatial data - Huixia Judy Wang (George Washington University)
DESCRIPTION:Abstract: Many existing methods for analyzing spatial data rely on the Gaussian assumption\, which is violated in many applications such as wind speed\, precipitation and COVID mortality data. In this talk\, I will discuss several semiparametric approaches for analyzing non-Gaussian spatial data through copula modeling. I will first present a copula-based...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11054
LOCATION:Maths 311B/Zoom
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11059@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230804T140000Z
DTEND:20230804T150000Z
SUMMARY:Statistics Seminar: Modelling spatiotemporal point patterns: a new era of point process models - Charlotte Jones-Todd (University of Auckland)
DESCRIPTION:Abstract: Modelling spatial and temporal patterns in ecology is imperative to understand the complex processes inherent in ecological phenomena. Log-Gaussian Cox processes are a popular choice amongst ecologists\, used to describe the spatiotemporal distribution of point-referenced data. In addition\, self-exciting point pattern models are becoming increasingly popular to infer the contagious...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11059
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11062@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230830T100000Z
DTEND:20230830T110000Z
SUMMARY:Statistics Seminar: Joint frailty modelling of time-to-event data with recurrent and terminal events - Shu-Kay Angus Ng (Griffith University)
DESCRIPTION:Abstract: We present an innovative perspective on analysing longitudinal data\, within a statistical framework of survival analysis of time-to-event recurrent data\, in order to elicit the evolution pathway of events of interest. The proposed methodology is based on a joint frailty modelling approach via a generalised linear mixed model (GLMM) formulation...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11062
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11081@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20231003T150000Z
DTEND:20231003T160000Z
SUMMARY:Statistics Seminar: Cross-validation for dependent data - Harvard Rue (KAUST)
DESCRIPTION:Abstract: I will discuss our new take on cross-validation (CV) for dependent data. Traditional use of CV\, like leave-one-out CV\, is justified using independence-like assumptions. With dependent data\, leave-one-out CV makes less sense\, as we are evaluating interpolation properties rather than prediction properties. We can adapt the CV idea to dependent...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11081
LOCATION:Joseph Black A504
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11064@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20231016T140000Z
DTEND:20231016T150000Z
SUMMARY:Statistics Seminar: Inferring the spatial distribution of visceral leishmaniasis burden in India - Emily Nightingale (London School of Hygiene and Tropical Medicine)
DESCRIPTION:Abstract: Visceral leishmaniasis (VL) is a debilitating and - without treatment - highly fatal disease which burdens impoverished communities in north-eastern India. Control and\, ultimately\, elimination of VL depends heavily on prompt case detection\, with delays contributing to persistence of transmission and the risk of resurgence in a population...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11064
LOCATION:Maths 311B
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11079@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20231023T080000Z
DTEND:20231023T120000Z
SUMMARY:SofTMech\, Statistics Seminar: Statistical Emulation for Computational Reverse Engineering and Translation - Various speakers
DESCRIPTION:Abstract: Workshop on computational tools for accurate\, robust and computationally efficient inference of unknown parameters in complex biophysical models from physiological data\, based on surrogate modelling and emulation. This is a workshop following on from an international competition that Mihaela has organised. It provides an excellent opportunity to learn more about...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11079
LOCATION:ARC\, Studio 2
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11077@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20231108T130000Z
DTEND:20231108T140000Z
SUMMARY:Statistics Seminar: A survival mixture cure model in smartphone-based earthquake early warning - Francesco Finazzi (University of Bergamo)
DESCRIPTION:Abstract: Crowdsourced smartphone-based earthquake early warning systems have recently emerged as reliable alternatives to more expensive solutions based on scientific instruments. During the deadly Turkish-Syrian event of 6 February 2023\, the system implemented by the Earthquake Network citizen science initiative provided up to 58 seconds of warning to people exposed to...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11077
LOCATION:Maths 311B
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11100@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20231129T140000Z
DTEND:20231129T150000Z
SUMMARY:Statistics Seminar: Bayesian graph-structured variable selection - Mahlet Tadesse (Georgetown University )
DESCRIPTION:Abstract: A graph structure is commonly used to characterize the dependence between variables\, which may be induced by time\, space\, biological networks or other factors. Incorporating this dependence structure into the model can increase the power to detect subtle effects without increasing the probability of false discoveries and can improve the predictive...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11100
LOCATION:Boyd Orr 409
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11111@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20231208T130000Z
DTEND:20231208T140000Z
SUMMARY:Statistics Seminar: Stats staff seminar - Philipp Otto & Isa Marques (University of Glasgow)
DESCRIPTION:Abstract: 1. Navigating Spatial Confounding: Understanding Causes and Proposing Future Approaches (Isa): Spatial confounding is a fundamental problem in regression models for spatially indexed data. It arises because spatial random effects\, which are included to approximate unmeasured spatial variation\, are typically not independent of the covariates...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11111
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11122@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240110T130000Z
DTEND:20240110T140000Z
SUMMARY:Statistics Seminar: TBA - Robin Long (Lancaster University)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11122
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11132@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240111T130000Z
DTEND:20240111T140000Z
SUMMARY:Statistics Seminar: TBA - Vianey Leos Barajas (University of Toronto)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11132
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11123@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240117T130000Z
DTEND:20240117T140000Z
SUMMARY:Statistics Seminar: TBA - Marian Scott and Xiaofei Zhang (University of Glasgow)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11123
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11080@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240124T130000Z
DTEND:20240124T140000Z
SUMMARY:Statistics Seminar: TBA - Mingshu Wang (University of Glasgow)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11080
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11091@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240207T130000Z
DTEND:20240207T140000Z
SUMMARY:Statistics Seminar: TBA - Amanda Lenzi (University of Edinburgh)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11091
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11112@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240221T130000Z
DTEND:20240221T140000Z
SUMMARY:Statistics Seminar: Statistics staff seminar - Claire Miller & Cao Pinna L (University of Glasgow)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11112
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11113@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240308T130000Z
DTEND:20240308T140000Z
SUMMARY:Statistics Seminar: TBA - Jafet Osuna & Janine Illian (University of Glasgow)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11113
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11125@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240322T130000Z
DTEND:20240322T140000Z
SUMMARY:Statistics Seminar: Recent Advances in Electricity Price Forecasting: A 2024 Perspective - Rafał Weron ( Wrocław University of Science and Technology)
DESCRIPTION:Abstract: Electricity price forecasting (EPF) is a branch of energy forecasting on the interface between econometrics/statistics\, computer science and engineering\, which focuses on predicting the spot and forward prices in wholesale electricity markets. Over the last 25 years\, a variety of methods and ideas have been tried for EPF\, with varying...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11125
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11124@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240403T120000Z
DTEND:20240403T130000Z
SUMMARY:Statistics Seminar: TBA - Dirk Husmeier (University of Glasgow)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11124
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11114@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20240503T120000Z
DTEND:20240503T130000Z
SUMMARY:Statistics Seminar: TBA - Eilidh Jack & Craig Anderson (University of Glasgow)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11114
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
END:VCALENDAR