33 citations · 66 across the 15 of their papers we have counts for
15 papers
Unsupervised anomaly detection in spatio-temporal stream network sensor data
Edgar Santos-Fernandez, Jay M. Ver Hoef, Erin E. Peterson +6
The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are…
Bayesian Design for Sampling Anomalous Spatio-Temporal Data
Katie Buchhorn, Kerrie Mengersen, Edgar Santos-Fernandez +1
Data collected from arrays of sensors are essential for informed decision-making in various systems. However, the presence of anomalies can compromise the accuracy and reliability…
Graph Neural Network-Based Anomaly Detection for River Network Systems
Katie Buchhorn, Edgar Santos-Fernandez, Kerrie Mengersen +1
Water is the lifeblood of river networks, and its quality plays a crucial role in sustaining both aquatic ecosystems and human societies. Real-time monitoring of water quality is i…
Conditional normalization in time series analysis
Puwasala Gamakumara, Edgar Santos-Fernandez, Priyanga Dilini Talagala +3
Time series often reflect variation associated with other related variables. Controlling for the effect of these variables is useful when modeling or analysing the time series. We…
Increasing trust in new data sources: crowdsourcing image classification for ecology
Edgar Santos-Fernandez, Julie Vercelloni, Aiden Price +4
Crowdsourcing methods facilitate the production of scientific information by non-experts. This form of citizen science (CS) is becoming a key source of complementary data in many f…
Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics
Joshua J. Bon, Adam Bretherton, Katie Buchhorn +12
Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most sta…
clusterBMA: Bayesian model averaging for clustering
Owen Forbes, Edgar Santos-Fernandez, Paul Pao-Yen Wu +7
Various methods have been developed to combine inference across multiple sets of results for unsupervised clustering, within the ensemble clustering literature. The approach of rep…
Bayesian Design with Sampling Windows for Complex Spatial Processes
Katie Buchhorn, Kerrie Mengersen, Edgar Santos-Fernandez +2
Optimal design facilitates intelligent data collection. In this paper, we introduce a fully Bayesian design approach for spatial processes with complex covariance structures, like…
On the intrinsic dimensionality of Covid-19 data: a global perspective
Abhishek Varghese, Edgar Santos-Fernandez, Francesco Denti +2
This paper aims to develop a global perspective of the complexity of the relationship between the standardised per-capita growth rate of Covid-19 cases, deaths, and the OxCGRT Covi…
SSNbayes: An R package for Bayesian spatio-temporal modelling on stream networks
Edgar Santos-Fernandez, Jay M. Ver Hoef, James M. McGree +3
Spatio-temporal models are widely used in many research areas from ecology to epidemiology. However, most covariance functions describe spatial relationships based on Euclidean dis…
Bayesian spatio-temporal models for stream networks
Edgar Santos-Fernandez, Jay M. Ver Hoef, Erin E. Peterson +3
Spatio-temporal models are widely used in many research areas including ecology. The recent proliferation of the use of in-situ sensors in streams and rivers supports space-time wa…
Correcting misclassification errors in crowdsourced ecological data: A Bayesian perspective
Edgar Santos-Fernandez, Erin E. Peterson, Julie Vercelloni +2
Many research domains use data elicited from "citizen scientists" when a direct measure of a process is expensive or infeasible. However, participants may report incorrect estimate…
Bayesian item response models for citizen science ecological data
Edgar Santos-Fernandez, Kerrie Mengersen
So-called 'citizen science' data elicited from crowds has become increasingly popular in many fields including ecology. However, the quality of this information is being frequently…
The role of intrinsic dimension in high-resolution player tracking data -- Insights in basketball
Edgar Santos-Fernandez, Francesco Denti, Kerrie Mengersen +1
A new range of statistical analysis has emerged in sports after the introduction of the high-resolution player tracking technology, specifically in basketball. However, this high d…
Monitoring through many eyes: Integrating disparate datasets to improve monitoring of the Great Barrier Reef
Erin E Peterson, Edgar Santos-Fernández, Carla Chen +13
Numerous organisations collect data in the Great Barrier Reef (GBR), but they are rarely analysed together due to different program objectives, methods, and data quality. We develo…