A general hidden state random walk model for animal movement

A general hidden state random walk model is proposed to describe the movement of an animal that takes into account movement taxis with respect to features of the environment. A circular–linear process models the direction and distance between two consecutive localizations of the animal. A hidden pro...

Full description

Bibliographic Details
Main Authors: Nicosia, Aurélien, Duchesne, Thierry, Rivest, Louis-Paul, Fortin, Daniel
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0167947316301736
id ftrepec:oai:RePEc:eee:csdana:v:105:y:2017:i:c:p:76-95
record_format openpolar
spelling ftrepec:oai:RePEc:eee:csdana:v:105:y:2017:i:c:p:76-95 2024-04-14T08:10:19+00:00 A general hidden state random walk model for animal movement Nicosia, Aurélien Duchesne, Thierry Rivest, Louis-Paul Fortin, Daniel http://www.sciencedirect.com/science/article/pii/S0167947316301736 unknown http://www.sciencedirect.com/science/article/pii/S0167947316301736 article ftrepec 2024-03-19T10:34:27Z A general hidden state random walk model is proposed to describe the movement of an animal that takes into account movement taxis with respect to features of the environment. A circular–linear process models the direction and distance between two consecutive localizations of the animal. A hidden process structure accounts for the animal’s change in movement behavior. The originality of the proposed approach is that several environmental targets can be included in the directional model. An EM algorithm that enables prediction of the hidden states of the process is devised to fit this model. An application to the analysis of the movement of caribou in Canada’s boreal forest is presented. Angular regression; Biased correlated random walk; Circular–linear process; Directional persistence; Directional statistical model; Filtering–smoothing algorithm; Markov model; Multi-state model; von Mises distribution; Article in Journal/Newspaper caribou RePEc (Research Papers in Economics)
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description A general hidden state random walk model is proposed to describe the movement of an animal that takes into account movement taxis with respect to features of the environment. A circular–linear process models the direction and distance between two consecutive localizations of the animal. A hidden process structure accounts for the animal’s change in movement behavior. The originality of the proposed approach is that several environmental targets can be included in the directional model. An EM algorithm that enables prediction of the hidden states of the process is devised to fit this model. An application to the analysis of the movement of caribou in Canada’s boreal forest is presented. Angular regression; Biased correlated random walk; Circular–linear process; Directional persistence; Directional statistical model; Filtering–smoothing algorithm; Markov model; Multi-state model; von Mises distribution;
format Article in Journal/Newspaper
author Nicosia, Aurélien
Duchesne, Thierry
Rivest, Louis-Paul
Fortin, Daniel
spellingShingle Nicosia, Aurélien
Duchesne, Thierry
Rivest, Louis-Paul
Fortin, Daniel
A general hidden state random walk model for animal movement
author_facet Nicosia, Aurélien
Duchesne, Thierry
Rivest, Louis-Paul
Fortin, Daniel
author_sort Nicosia, Aurélien
title A general hidden state random walk model for animal movement
title_short A general hidden state random walk model for animal movement
title_full A general hidden state random walk model for animal movement
title_fullStr A general hidden state random walk model for animal movement
title_full_unstemmed A general hidden state random walk model for animal movement
title_sort general hidden state random walk model for animal movement
url http://www.sciencedirect.com/science/article/pii/S0167947316301736
genre caribou
genre_facet caribou
op_relation http://www.sciencedirect.com/science/article/pii/S0167947316301736
_version_ 1796307845635899392