238 related articles for article (PubMed ID: 26485953)
1. Objective classification of latent behavioral states in bio-logging data using multivariate-normal hidden Markov models.
Phillips JS; Patterson TA; Leroy B; Pilling GM; Nicol SJ
Ecol Appl; 2015 Jul; 25(5):1244-58. PubMed ID: 26485953
[TBL] [Abstract][Full Text] [Related]
2. Classifying movement behaviour in relation to environmental conditions using hidden Markov models.
Patterson TA; Basson M; Bravington MV; Gunn JS
J Anim Ecol; 2009 Nov; 78(6):1113-23. PubMed ID: 19563470
[TBL] [Abstract][Full Text] [Related]
3. Dynamic optimal foraging theory explains vertical migrations of Bigeye tuna.
Thygesen UH; Sommer L; Evans K; Patterson TA
Ecology; 2016 Jul; 97(7):1852-1861. PubMed ID: 27859170
[TBL] [Abstract][Full Text] [Related]
4. Coupling spectral analysis and hidden Markov models for the segmentation of behavioural patterns.
Heerah K; Woillez M; Fablet R; Garren F; Martin S; De Pontual H
Mov Ecol; 2017; 5():20. PubMed ID: 28944062
[TBL] [Abstract][Full Text] [Related]
5. Hidden Markov models identify major movement modes in accelerometer and magnetometer data from four albatross species.
Conners MG; Michelot T; Heywood EI; Orben RA; Phillips RA; Vyssotski AL; Shaffer SA; Thorne LH
Mov Ecol; 2021 Feb; 9(1):7. PubMed ID: 33618773
[TBL] [Abstract][Full Text] [Related]
6. How to account for behavioral states in step-selection analysis: a model comparison.
Pohle J; Signer J; Eccard JA; Dammhahn M; Schlägel UE
PeerJ; 2024; 12():e16509. PubMed ID: 38426131
[TBL] [Abstract][Full Text] [Related]
7. Predicting feeding success in a migratory predator: integrating telemetry, environment, and modeling techniques.
Bestley S; Patterson TA; Hindell MA; Gunn JS
Ecology; 2010 Aug; 91(8):2373-84. PubMed ID: 20836459
[TBL] [Abstract][Full Text] [Related]
8. Unsupervised Estimation of Mouse Sleep Scores and Dynamics Using a Graphical Model of Electrophysiological Measurements.
Yaghouby F; O'Hara BF; Sunderam S
Int J Neural Syst; 2016 Jun; 26(4):1650017. PubMed ID: 27121993
[TBL] [Abstract][Full Text] [Related]
9. Nonparametric inference in hidden Markov models using P-splines.
Langrock R; Kneib T; Sohn A; DeRuiter SL
Biometrics; 2015 Jun; 71(2):520-8. PubMed ID: 25586063
[TBL] [Abstract][Full Text] [Related]
10. Handling underlying discrete variables with bivariate mixed hidden Markov models in NONMEM.
Brekkan A; Jönsson S; Karlsson MO; Plan EL
J Pharmacokinet Pharmacodyn; 2019 Dec; 46(6):591-604. PubMed ID: 31654267
[TBL] [Abstract][Full Text] [Related]
11. Hidden Markov models reveal complexity in the diving behaviour of short-finned pilot whales.
Quick NJ; Isojunno S; Sadykova D; Bowers M; Nowacek DP; Read AJ
Sci Rep; 2017 Mar; 7():45765. PubMed ID: 28361954
[TBL] [Abstract][Full Text] [Related]
12. Flexible hidden Markov models for behaviour-dependent habitat selection.
Klappstein NJ; Thomas L; Michelot T
Mov Ecol; 2023 Jun; 11(1):30. PubMed ID: 37270509
[TBL] [Abstract][Full Text] [Related]
13. Revisiting the vulnerability of juvenile bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna caught by purse-seine fisheries while associating with surface waters and floating objects.
Scutt Phillips J; Pilling GM; Leroy B; Evans K; Usu T; Lam CH; Schaefer KM; Nicol S
PLoS One; 2017; 12(6):e0179045. PubMed ID: 28662091
[TBL] [Abstract][Full Text] [Related]
14. Population assessment of tropical tuna based on their associative behavior around floating objects.
Capello M; Deneubourg JL; Robert M; Holland KN; Schaefer KM; Dagorn L
Sci Rep; 2016 Nov; 6():36415. PubMed ID: 27808175
[TBL] [Abstract][Full Text] [Related]
15. Hidden Markov Models Capture Behavioral Responses to Suction-Cup Tag Deployment: A Functional State Approach to Behavioral Context.
Isojunno S; Miller PJ
Adv Exp Med Biol; 2016; 875():489-96. PubMed ID: 26610996
[TBL] [Abstract][Full Text] [Related]
16. Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions.
Langrock R; King R; Matthiopoulos J; Thomas L; Fortin D; Morales JM
Ecology; 2012 Nov; 93(11):2336-42. PubMed ID: 23236905
[TBL] [Abstract][Full Text] [Related]
17. From forager tracks to prey distributions: an application to tuna vessel monitoring systems (VMS).
Walker E; Rivoirard J; Gaspar P; Bez N
Ecol Appl; 2015 Apr; 25(3):826-33. PubMed ID: 26214926
[TBL] [Abstract][Full Text] [Related]
18. Incorporating periodic variability in hidden Markov models for animal movement.
Li M; Bolker BM
Mov Ecol; 2017; 5():1. PubMed ID: 28149522
[TBL] [Abstract][Full Text] [Related]
19. Scaling marine fish movement behavior from individuals to populations.
Griffiths CA; Patterson TA; Blanchard JL; Righton DA; Wright SR; Pitchford JW; Blackwell PG
Ecol Evol; 2018 Jul; 8(14):7031-7043. PubMed ID: 30073065
[TBL] [Abstract][Full Text] [Related]
20. Simulation of large-scale tropical tuna movements in relation with daily remote sensing data: the artificial life approach.
Dagorn L; Petit M; Stretta JM
Biosystems; 1997; 44(3):167-80. PubMed ID: 9460558
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]