Nancy Heckman, University of British Columbia

Research

animal movement classification functional data analysis hidden Markov models latent states penalized B-splines

Latest papers

Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.
PloS one · 2025
Killer whale respiration rates.
PloS one · 2024
Rapid adaptive evolution of colour vision in the threespine stickleback radiation.
Proceedings. Biological sciences · 2016

All 3 publications

Latest funding

Canadian Statistical Sciences Institute DIS Bridge Funding Proposal
NSERC · 2021 · Co-investigator
$483,760
Functional Data Analysis, Mixed Models and Hidden Markov Models
NSERC · 2020 · Principal investigator
$162,000
Testing whether the Availability of Chinook Salmon is Insufficient to Support a Healthy Southern Resident Killer Whale Population
NSERC · 2018 · Co-investigator
$100,000

All 16 grants and awards

3 publications.

01

Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.

Sidrow E, Heckman N, McRae TM, Volpov BL, Trites AW, Fortune SME, Auger-Méthé M

PloS one2025

DOI: 10.1371/journal.pone.0325321 PMID: 40531913

02

Killer whale respiration rates.

McRae TM, Volpov BL, Sidrow E, Fortune SME, Auger-Méthé M, Heckman N, Trites AW

PloS one2024

DOI: 10.1371/journal.pone.0302758 PMID: 38748652

03

Rapid adaptive evolution of colour vision in the threespine stickleback radiation.

Rennison DJ, Owens GL, Heckman N, Schluter D, Veen T

Proceedings. Biological sciences2016

DOI: 10.1098/rspb.2016.0242 PMID: 27147098

Canadian Statistical Sciences Institute DIS Bridge Funding Proposal

Co-investigatorNSERC2021Discovery Institutes Support Grants Bridge Funding Opportunity

Principal investigators: Estep, Donald

$483,760

Functional Data Analysis, Mixed Models and Hidden Markov Models

Principal investigatorNSERC2020Discovery Grants Program - Individual

Principal investigators: Heckman, Nancy

Keywords: functional data analysis; latent states; classification; animal movement; hidden markov models; penalized b-splines

$162,000

Testing whether the Availability of Chinook Salmon is Insufficient to Support a Healthy Southern Resident Killer Whale Population

Co-investigatorNSERC2018Whale Science for Tomorrow

Principal investigators: Trites, Andrew

$100,000

Forest products stochastic modelling group: advanced manufacturing and product development

Co-investigatorNSERC2014Collaborative Research and Development Grants

Principal investigators: Zidek, James

$200,000

Methodological Development of Functional Data Analysis, with Applications

Principal investigatorNSERC2013Discovery Grants Program - Individual

Principal investigators: Heckman, Nancy

$55,000

Forest products stochastic modeling group

Co-investigatorNSERC2009Collaborative Research and Development Grants

Principal investigators: Zidek, James

$490,000

Functional data analysis

Principal investigatorNSERC2007Discovery Grants Program - Individual

Principal investigators: Heckman, Nancy

$135,000

Computing network at dept. of statistics UBC

Co-investigatorNSERC2005Research Tools and Instruments - Category 1 (<$150,000)

Principal investigators: Joe, Harry

$27,750

Functional data analysis/studing families of smooth curves

Principal investigatorNSERC2003Discovery Grants Program - Individual

Principal investigators: Heckman, Nancy

$104,000

Research computing network in the department of statistics at u.b.c

Co-investigatorNSERC2003Research Tools and Instruments - Category 1 (<$150,000)

Principal investigators: Zamar, Ruben

$45,038

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

Frequent collaborators

Dolph Schluter

Department of Zoology

1 shared papers, latest 2016

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their NSERC grant from 2020

Subject: Prospective PhD student: animal movement Dear Professor Heckman, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies." (2025), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Functional Data Analysis, Mixed Models and Hidden Markov Models" (2020), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]