The Canadian Journal of Statistics Award 2023

Evan Sidrow
Nancy Heckman
Sarah M. E. Fortune
Andrew Trites
Ian Murphy
Marie Auger-Méthé
The Canadian Journal of Statistics Award
“Modelling multi-scale, state-switching functional data with hidden Markov models”, which appeared in 2022, volume 50, no. 1, pages 327-356.

The Canadian Journal of Statistics Award is awarded annually by the SSC to the author(s) of an article published in the previous year in the journal, in recognition of the outstanding quality of the paper's methodological innovation and presentation. 

Evan Sidrow is a PhD student in Statistics in the Department of Statistics, University of British Columbia. Evan is doing a PhD developing statistical methodology to help analyse a broad range of data, including high-frequency biotelemetry data. He is interested in developing hidden Markov models that help identify behavioural states, and computational techniques to increase the efficiency of complex model fitting. He works on a large collaborative project trying to identify why southern resident killer whales are in worse condition than their neighbours, the northern residents. He is co-supervised by Dr. Marie Auger-Méthé and Dr. Nancy Heckman.

Nancy Heckman is a Professor Emeritus in the Department of Statistics, University of British Columbia. Her research interests include, but not limited to functional data analysis and applications to evolutionary biology, nonparametric regression via splines, kernels and local polynomials; shapes of regression functions. Professor Heckman has used functional data analysis techniques in many application areas.  She has worked with evolutionary biologists on a range of projects, developing and applying statistical methods to study the evolution of physical traits that are functions. Professor Heckman has several co-authored papers on developing functional data analysis techniques for the analysis of energy consumption, where each curve gives energy consumed as a function of time. Recently, she has become involved with collaborative research on animal movement, using hidden Markov models.

Sarah M. E. Fortune is with the Marine Mammal Research Unit, University of British Columbia. Sarah is interested in understanding the complex feeding dynamics of marine mammals in temperate and Arctic environments. Her research focuses on determining the biological and physical conditions necessary to support successful feeding under current environmental conditions. Sarah applies new technology to record the fine-scale movements of large whales from the air and underwater to determine when and where they are feeding and what their encountered prey field looks like.

Andrew Trites is a Professor and Director of the Marine Mammal Research Unit in the Institute for the Oceans and Fisheries at the University of British Columbia. He has been studying marine mammals in the North Pacific for 40 years, and leads a research program designed to further the conservation and understanding of marine mammals, and resolve conflicts between people and marine mammals.  He has served on many advisory committees and independent panels that involve marine mammals and species at risk.

Ian Murphy is a PhD student in the Department of Biostatistics, in the College of Public Health and Health Professions, at the University of Florida in Gainesville, Florida, where he has been since 2021. Ian completed his Master's of Science in Statistics at the University of British Columbia in 2021, and he completed his Bachelor's of Mathematics in Applied Math and Statistics at the University of Waterloo in 2019. His main research interests currently revolve around developing statistical methods to deal with high dimensional, longitudinal microbiome data. He also teaches Masters-level courses in biostatistics at the University of Florida, ranging from theoretical statistics to applied statistics for health science students. 

Marie Auger-Méthé is an Associate Professor in the Department of Statistics, Institute for the Oceans & Fisheries, University of British Columbia. She is broadly interested in developing and applying statistical tools to infer behavioural and population processes from empirical data. Her work tends to focus on marine and polar animals, but the methods she develops are often applicable to a wide range of species and ecosystems. Her recent work has centred on modelling animal behaviour using movement data and developing hierarchical models for spatial and/or temporal data. 

The citation for the award reads: 

The article entitled "Modelling multi-scale, state-switching functional data with hidden Markov models" by Evan Sidrow, Nancy Heckman, Sarah M. E. Fortune, Andrew W. Trites, Ian Murphy, and Marie Auger-Méthé is recognized for creativity, excellence, and presentation.

The article investigates how to identify and describe discrete states within functional data and to model the dependence structure between these states. The hidden Markov model technique is applied. The article elegantly combines the theoretical findings with deep practical applications to the fine-scale kinematic movements of a northern resident killer whale (Orcinus orca) off the western coast of Canada.

Andrei Volodin was primarily responsible for producing this material.