A primer on coupled state-switching models for multiple interacting time series

State-switching models such as hidden Markov models or Markov-switching regression models are routinely applied to analyse sequences of observations that are driven by underlying non-observable states. Coupled state-switching models extend these approaches to address the case of multiple observation sequences whose underlying state variables interact. In this paper, we provide an overview of the modelling techniques related to coupling in state-switching models, thereby forming a rich and flexible statistical framework particularly useful for modelling correlated time series. Simulation experiments demonstrate the relevance of being able to account for an asynchronous evolution as well as interactions between the underlying latent processes. The models are further illustrated using two case studies related to a) interactions between a dolphin mother and her calf as inferred from movement data; and b) electronic health record data collected on 696 patients within an intensive care unit.Comment: 30 pages, 9 figure

Inferring the unobservable - identifying state architectures in hidden Markov models

Pohle JM. Inferring the unobservable - identifying state architectures in hidden Markov models. Bielefeld: Universität Bielefeld; 2022

Pragmatic order selection in hidden Markov models

Pohle JM, Langrock R. Pragmatic order selection in hidden Markov models. In: Proceedings of the 32nd IWSM Vol. 1. 2017

Sex-specific variation in the use of vertical habitat by a resident Antarctic top predator

Funding: The data collection was funded by NERC grant nos NE/G014833/1 and NE/G014086/1. T.P. was supported by a Royal Society Newton International Fellowship (NF170682). K.H. was supported by a Marie-Skłodowska Curie Research Fellowship.Patterns of habitat use are commonly studied in horizontal space, but this does not capture the four-dimensional nature of ocean habitats (space, depth, and time). Deep-diving marine animals encounter varying oceanographic conditions, particularly at the poles, where there is strong seasonal variation in vertical ocean structuring. This dimension of space use is hidden if we only consider horizontal movement. To identify different diving behaviours and usage patterns of vertically distributed habitat, we use hidden Markov models fitted to telemetry data from an air-breathing top predator, the Weddell seal, in the Weddell Sea, Antarctica. We present evidence of overlapping use of high-density, continental shelf water masses by both sexes, as well as important differences in their preferences for oceanographic conditions. Males spend more time in the unique high-salinity shelf water masses found at depth, while females also venture off the continental shelf and visit warmer, shallower water masses. Both sexes exhibit a diurnal pattern in diving behaviour (deep in the day, shallow at night) that persists from austral autumn into winter. The differences in habitat use in this resident, sexually monomorphic Antarctic top predator suggest a different set of needs and constraints operating at the intraspecific level, not driven by body size.Publisher PDFPeer reviewe

Modeling interactions between individuals using coupled hidden Markov models

Pohle JM, Ötting M, Jensen FH, Langrock R. Modeling interactions between individuals using coupled hidden Markov models. In: Proceedings of the 34th International Workshop on Statistical Modelling. Volume I. 2019: 57-61

Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement

Pohle J, Langrock R, van Beest FM, Schmidt NM. Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement. Journal of Agricultural, Biological and Environmental Statistics. 2017;22(3):270–293