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Hidden Markov models (HMMs) have been used increasingly to understand how movement patterns of animals arise from behavioural states. An animal is assumed to transition between behavioural states through time, as described by transition…

Quantitative Methods · Quantitative Biology 2025-10-07 Théo Michelot , Emma Storey

While non-invasive sampling is more and more commonly used in capture-recapture (CR) experiments, it carries a higher risk of misidentifications than direct observations. As a consequence, one must screen the data to retain only the…

Quantitative Methods · Quantitative Biology 2023-04-04 Rémi Fraysse , Rémi Choquet , Carlo Costantini , Roger Pradel

Advances in field techniques have lead to an increase in spatially-referenced capture-recapture data to estimate a species' population size as well as other demographic parameters and patterns of space usage. Statistical models for these…

Applications · Statistics 2014-05-09 Brian J. Reich , Beth Gardner

A multi-state version of an animal movement analysis method based on conditional logistic regression, called Step Selection Function (SSF), is proposed. In ecology SSF is developed from a comparison between the observed location of an…

Methodology · Statistics 2018-03-14 Aurélien Nicosia , Thierry Duchesne , Louis-Paul Rivest , Daniel Fortin

Molecular simulations can provide microscopic insight into the physical and chemical driving forces of complex molecular processes. Despite continued advancement of simulation methodology, model errors may lead to inconsistencies between…

Chemical Physics · Physics 2016-02-12 Joseph F. Rudzinski , Kurt Kremer , Tristan Bereau

Automated animal behavior analysis relies on long-term, interpretable individual trajectories; however, multi-animal tracking in space science experimental videos remains highly challenging due to weak appearance cues, low-quality imaging,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Jianing You , Han Wang , Kang Liu , Jiale Ding , Fengjie Chu , Zihan Guo , Shengyang Li

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 devices such as video recorders and drones now allow…

Markov models have been widely utilized for modelling user web navigation behaviour. In this work we propose a dynamic clustering-based method to increase a Markov model's accuracy in representing a collection of user web navigation…

Information Retrieval · Computer Science 2007-05-23 José Borges , Mark Levene

We consider first the mixed discrete-continuous scheme of observation in multistate models; this is a classical pattern in epidemiology because very often clinical status is assessed at discrete visit times while times of death or other…

Statistics Theory · Mathematics 2008-12-18 Daniel Commenges , Anne Gégout-Petit

Continuous-time multi-state survival models can be used to describe health-related processes over time. In the presence of interval-censored times for transitions between the living states, the likelihood is constructed using transition…

Methodology · Statistics 2017-03-24 Robson J. M. Machado , Ardo van den Hout

Dynamic networks exhibit temporal patterns that vary across different time scales, all of which can potentially affect processes that take place on the network. However, most data-driven approaches used to model time-varying networks…

Physics and Society · Physics 2017-12-27 Tiago P. Peixoto , Laetitia Gauvin

We address tracking and prediction of multiple moving objects in visual data streams as inference and sampling in a disentangled latent state-space model. By encoding objects separately and including explicit position information in the…

Machine Learning · Statistics 2019-10-15 Adnan Akhundov , Maximilian Soelch , Justin Bayer , Patrick van der Smagt

A state-space model is a time-series model that has an unobserved latent process from which we take noisy measurements over time. The observations are conditionally independent given the latent process and the latent process itself is…

Methodology · Statistics 2025-10-07 Paul Fearnhead , Chris Sherlock

In time domain astronomy, recurrent transients present a special problem: how to infer total populations from limited observations. Monitoring observations may give a biassed view of the underlying population due to limitations on observing…

High Energy Astrophysical Phenomena · Physics 2017-02-08 Silas G. T. Laycock

In the companion paper of this set (Capitan and Cuesta, 2010) we have developed a full analytical treatment of the model of species assembly introduced in Capitan et al. (2009). This model is based on the construction of an assembly graph…

Populations and Evolution · Quantitative Biology 2015-02-18 Jose A. Capitan , Jose A. Cuesta , Jordi Bascompte

State-space models are important tools for quality control of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system aids dynamic ocean management of human activities by informing when…

Data collected from wearable devices and smartphones can shed light on an individual's pattern of behavioral and circadian routine. Phone use can be modeled as alternating event process, between the state of active use and the state of…

Methodology · Statistics 2022-12-13 Benny Ren , Ian Barnett

Capture-recapture studies are widely used to obtain information about abundance (population size or density) of animal populations. A common design is that in which multiple distinct populations are sampled, and the research objective is…

Methodology · Statistics 2012-11-27 J. Andrew Royle , Sarah J. Converse , William A. Link

Experiments, in particular on biological systems, typically probe lower-dimensional observables which are projections of high-dimensional dynamics. In order to infer consistent models capturing the relevant dynamics of the system, it is…

Statistical Mechanics · Physics 2025-11-18 Xizhu Zhao , Dmitrii E. Makarov , Aljaž Godec

Under certain conditions, the dynamics of coarse-grained models of solvated proteins can be described using a Markov state model, which tracks the evolution of populations of configurations. The transition rates among states that appear in…

Soft Condensed Matter · Physics 2022-09-26 Margarita Colberg , Jeremy Schofield
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