18 citations · 21 across the 4 of their papers we have counts for
4 papers
Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies
Evan Sidrow, Nancy Heckman, Tess M. McRae +4
Ecologists often use a hidden Markov model to decode a latent process, such as a sequence of an animal's behaviours, from an observed biologging time series. Modern technological d…
An introduction to statistical models used to characterize species-habitat associations with animal movement data
Katie R. N. Florko, Ron R. Togunov, Rowenna Gryba +4
Understanding species-habitat associations is fundamental to ecological sciences and for species conservation. Consequently, various statistical approaches have been designed to in…
Variance-Reduced Stochastic Optimization for Efficient Inference of Hidden Markov Models
Evan Sidrow, Nancy Heckman, Alexandre Bouchard-Côté +3
Hidden Markov models (HMMs) are popular models to identify a finite number of latent states from sequential data. However, fitting them to large data sets can be computationally de…
Modelling multi-scale state-switching functional data with hidden Markov models
Evan Sidrow, Nancy Heckman, Sarah M. E. Fortune +3
Data sets comprised of sequences of curves sampled at high frequencies in time are increasingly common in practice, but they can exhibit complicated dependence structures that cann…