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
Théo MichelotDalhousie UniversityVerified email at dal.ca
Len ThomasUniversity of St AndrewsVerified email at st-andrews.ac.uk
Floris M. van BeestSenior Researcher, Department of Bioscience, Aarhus UniversityVerified email at bios.au.dk
Sina MewsPhD student in Statistics, Bielefeld UniversityVerified email at uni-bielefeld.de
Timo AdamUniversity of Copenhagen, Department of Mathematical SciencesVerified email at math.ku.dk
Marius ÖttingPostdoc at Bielefeld UniversityVerified email at uni-bielefeld.de
Jennifer PohleUniversity of PotsdamVerified email at uni-potsdam.de
Yannis PapastamatiouAssociate Professor, Florida International UniversityVerified email at fiu.edu
David BorchersUniversity of St AndrewsVerified email at st-andrews.ac.uk
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
Juan M. MoralesSBOHVM, University of GlasgowVerified email at glasgow.ac.uk
Niels Martin SchmidtProfessor at Aarhus University, DenmarkVerified email at bios.au.dk
Christian DeutscherProfessor for Sports Economics, Bielefeld UniversityVerified email at uni-bielefeld.de
Robert SchickMarine Geospatial Ecology Laboratory, Nicholas School of the Environment, Duke UniversityVerified email at duke.edu
Theoni PhotopoulouResearch Fellow, University of St AndrewsVerified email at st-andrews.ac.uk
Yuuki WatanabeResearch Center for Integrative Evolutionary Science, The Graduate University for Advanced StudiesVerified email at soken.ac.jp

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	1502	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	397	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	328	2016
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	208*	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	172	2017
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	140	2017
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	107	2014
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	106*	2017
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	105	2022
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	101	2016
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	98	2020
Hidden Markov models with arbitrary state dwell-time distributions R Langrock, W Zucchini Computational Statistics & Data Analysis 55 (1), 715-724, 2011	75	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	73	2015
Estimation and simulation of foraging trips in land-based marine predators T Michelot, R Langrock, S Bestley, ID Jonsen, T Photopoulou, ... Ecology, 2017	67	2017
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	64	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	64	2013
Nonparametric inference in hidden Markov models using P-splines R Langrock, T Kneib, A Sohn, SL DeRuiter Biometrics 71 (2), 520-528, 2015	63	2015
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	62	2018
Some nonstandard stochastic volatility models and their estimation using structured hidden Markov models R Langrock, IL MacDonald, W Zucchini Journal of Empirical Finance 19 (1), 147-161, 2011	56	2011
On the application of mixed hidden Markov models to multiple behavioural time series S Schliehe-Diecks, PM Kappeler, R Langrock Interface Focus 2, 180-189, 2012	54	2012

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