Roland Langrock

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Ruth KingThomas Bayes' Chair of Statistics, University of EdinburghVerified email at ed.ac.uk
Toby PattersonCSIRO Verified email at csiro.au
Vianey Leos BarajasUniversity of TorontoVerified email at utoronto.ca
Sina MewsPhD student in Statistics, Bielefeld UniversityVerified email at uni-bielefeld.de
Théo MichelotDalhousie UniversityVerified email at dal.ca
Marius ÖttingData Scientist in InsuranceVerified email at uni-bielefeld.de
Len ThomasCREEM, University of St AndrewsVerified email at st-andrews.ac.uk
Timo AdamBielefeld UniversityVerified email at uni-bielefeld.de
Floris M. van BeestAssociate Professor (Senior Researcher), Department of Ecoscience, Aarhus UniversityVerified email at bios.au.dk
Jennifer PohleUniversity of PotsdamVerified email at uni-potsdam.de
David BorchersCREEM, University of St AndrewsVerified email at st-andrews.ac.uk
Yannis PapastamatiouAssociate Professor, Florida International UniversityVerified email at fiu.edu
Thomas KneibChair of Statistics, Georg-August-University GöttingenVerified email at uni-goettingen.de
Stacy DeRuiterDepartment of Mathematics and Statistics, Calvin UniversityVerified email at calvin.edu
Christian DeutscherBielefeld UniversityVerified email at uni-bielefeld.de
Niels Martin SchmidtProfessor at Aarhus University, DenmarkVerified email at bios.au.dk
Juan M. MoralesSBOHVM, University of GlasgowVerified email at glasgow.ac.uk
Yuuki WatanabeResearch Center for Integrative Evolutionary Science, The Graduate University for Advanced StudiesVerified email at soken.ac.jp
Theoni PhotopoulouResearch Fellow, University of St AndrewsVerified email at st-andrews.ac.uk
Robert SchickMarine Geospatial Ecology Laboratory, Nicholas School of the Environment, Duke UniversityVerified email at duke.edu

Roland Langrock

Statistics and Data Analysis group, Bielefeld University

Verified email at uni-bielefeld.de - Homepage

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Hidden Markov Models for Time Series: An Introduction Using R W Zucchini, IL MacDonald, R Langrock	1773*	2016
Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions R Langrock, R King, J Matthiopoulos, L Thomas, D Fortin, JM Morales Ecology 93 (11), 2336-2342, 2012	483	2012
moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models T Michelot, R Langrock, TA Patterson Methods in Ecology and Evolution 7 (11), 1308-1315, 2016	413	2016
Big-data approaches lead to an increased understanding of the ecology of animal movement R Nathan, CT Monk, R Arlinghaus, T Adam, J Alós, M Assaf, H Baktoft, ... Science 375 (6582), eabg1780, 2022	325	2022
Selecting the number of states in hidden Markov models — pragmatic solutions illustrated using animal movement J Pohle, R Langrock, F van Beest, NM Schmidt Journal of Agricultural, Biological, and Environmental Statistics, 2017	282	2017
Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges TA Patterson, A Parton, R Langrock, PG Blackwell, L Thomas, R King AStA Advances in Statistical Analysis, 2017	217	2017
Uncovering ecological state dynamics with hidden Markov models BT McClintock, R Langrock, O Gimenez, E Cam, DL Borchers, R Glennie, ... Ecology Letters 23 (12), 1878-1903, 2020	184	2020
Analysis of animal accelerometer data using hidden Markov models V Leos‐Barajas, T Photopoulou, R Langrock, TA Patterson, YY Watanabe, ... Methods in Ecology and Evolution 8 (2), 161-173, 2017	182	2017
A multivariate mixed hidden Markov model for blue whale behaviour and responses to sound exposure SL DeRuiter, R Langrock, T Skirbutas, JA Goldbogen, J Chalambokidis, ... The Annals of Applied Statistics 11 (1), 362-392, 2017	130*	2017
Sex‐specific and individual preferences for hunting strategies in white sharks AV Towner, V Leos‐Barajas, R Langrock, RS Schick, MJ Smale, ... Functional Ecology 30, 1397-1407, 2016	119	2016
Modelling group dynamic animal movement R Langrock, G Hopcraft, P Blackwell, V Goodall, R King, M Niu, ... Methods in Ecology and Evolution 5 (2), 190-199, 2014	117	2014
Multi-scale modeling of animal movement and general behavior data using hidden Markov models with hierarchical structures V Leos-Barajas, EJ Gangloff, T Adam, R Langrock, FM Van Beest, ... Journal of Agricultural, Biological and Environmental Statistics 22, 232-248, 2017	83	2017
Activity seascapes highlight central place foraging strategies in marine predators that never stop swimming YP Papastamatiou, YY Watanabe, U Demšar, V Leos-Barajas, D Bradley, ... Movement Ecology 6 (1), 9, 2018	81	2018
Hidden Markov models with arbitrary state dwell-time distributions R Langrock, W Zucchini Computational Statistics & Data Analysis 55 (1), 715-724, 2011	81	2011
Using mixed hidden Markov models to examine behavioral states in a cooperatively breeding bird AE McKellar, R Langrock, JR Walters, DC Kesler Behavioral Ecology 26 (1), 148-157, 2015	78	2015
Estimation and simulation of foraging trips in land-based marine predators T Michelot, R Langrock, S Bestley, ID Jonsen, T Photopoulou, ... Ecology, 2017	75	2017
Using hidden Markov models to deal with availability bias on line transect surveys D Borchers, W Zucchini, M Heide-Jorgensen, A Canadas, R Langrock Biometrics 69 (3), 703-713, 2013	73	2013
Nonparametric inference in hidden Markov models using P-splines R Langrock, T Kneib, A Sohn, SL DeRuiter Biometrics 71 (2), 520-528, 2015	70	2015
Joint modelling of multi‐scale animal movement data using hierarchical hidden Markov models T Adam, CA Griffiths, V Leos‐Barajas, EN Meese, CG Lowe, PG Blackwell, ... Methods in Ecology and Evolution, 2019	69	2019
Classifying grey seal behaviour in relation to environmental variability and commercial fishing activity-a multivariate hidden Markov model FM van Beest, S Mews, S Elkenkamp, P Schuhmann, D Tsolak, T Wobbe, ... Scientific Reports 9 (1), 5642, 2019	67	2019

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