Estimating distance sampling detection functions when distances are measured with errors
Distance sampling methods assume that distances are known but in practice there are often errors in measuring them. These can have substantial impact on the bias and precision of distance sampling estimators. In this paper we develop methods that accommodate both systematic and stochastic measuremen...
Published in: | Journal of Agricultural, Biological, and Environmental Statistics |
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ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/7cd2ee12-37fb-44d8-9f09-a13f58ab482a 2023-05-15T16:50:26+02:00 Estimating distance sampling detection functions when distances are measured with errors Borchers, David Marques, Tiago Gunnlaugsson, Thorvaldur Jupp, Peter 2010-09 https://risweb.st-andrews.ac.uk/portal/en/researchoutput/estimating-distance-sampling-detection-functions-when-distances-are-measured-with-errors(7cd2ee12-37fb-44d8-9f09-a13f58ab482a).html https://doi.org/10.1007/s13253-010-0021-y http://www.scopus.com/inward/record.url?scp=77949559081&partnerID=8YFLogxK eng eng info:eu-repo/semantics/restrictedAccess Borchers , D , Marques , T , Gunnlaugsson , T & Jupp , P 2010 , ' Estimating distance sampling detection functions when distances are measured with errors ' , Journal of Agricultural, Biological and Environmental Statistics , vol. 15 , no. 3 , pp. 346-361 . https://doi.org/10.1007/s13253-010-0021-y article 2010 ftunstandrewcris https://doi.org/10.1007/s13253-010-0021-y 2022-06-02T07:39:48Z Distance sampling methods assume that distances are known but in practice there are often errors in measuring them. These can have substantial impact on the bias and precision of distance sampling estimators. In this paper we develop methods that accommodate both systematic and stochastic measurement errors. We use the methods to estimate detection probability in two surveys with substantial measurement error. The first is a shipboard line transect survey in the North Sea in which information on measurement error comes from photographically measured distances to a subset of detections. The second is an aerial cue-counting survey off Iceland in which information on measurement error comes from pairs of independently estimated distances to a subset of detections. Different methods are required for measurement error estimation in the two cases. We investigate by simulation the properties of the new estimators and compare them to conventional estimators. They are found to perform better than conventional estimators in the presence of measurement error, more so in the case of cue-counting and point transect estimators than line transect estimators. An appendix on the asymptotic distributions of conditional and full likelihood estimators is available online. Article in Journal/Newspaper Iceland University of St Andrews: Research Portal Journal of Agricultural, Biological, and Environmental Statistics 15 3 346 361 |
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University of St Andrews: Research Portal |
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ftunstandrewcris |
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English |
description |
Distance sampling methods assume that distances are known but in practice there are often errors in measuring them. These can have substantial impact on the bias and precision of distance sampling estimators. In this paper we develop methods that accommodate both systematic and stochastic measurement errors. We use the methods to estimate detection probability in two surveys with substantial measurement error. The first is a shipboard line transect survey in the North Sea in which information on measurement error comes from photographically measured distances to a subset of detections. The second is an aerial cue-counting survey off Iceland in which information on measurement error comes from pairs of independently estimated distances to a subset of detections. Different methods are required for measurement error estimation in the two cases. We investigate by simulation the properties of the new estimators and compare them to conventional estimators. They are found to perform better than conventional estimators in the presence of measurement error, more so in the case of cue-counting and point transect estimators than line transect estimators. An appendix on the asymptotic distributions of conditional and full likelihood estimators is available online. |
format |
Article in Journal/Newspaper |
author |
Borchers, David Marques, Tiago Gunnlaugsson, Thorvaldur Jupp, Peter |
spellingShingle |
Borchers, David Marques, Tiago Gunnlaugsson, Thorvaldur Jupp, Peter Estimating distance sampling detection functions when distances are measured with errors |
author_facet |
Borchers, David Marques, Tiago Gunnlaugsson, Thorvaldur Jupp, Peter |
author_sort |
Borchers, David |
title |
Estimating distance sampling detection functions when distances are measured with errors |
title_short |
Estimating distance sampling detection functions when distances are measured with errors |
title_full |
Estimating distance sampling detection functions when distances are measured with errors |
title_fullStr |
Estimating distance sampling detection functions when distances are measured with errors |
title_full_unstemmed |
Estimating distance sampling detection functions when distances are measured with errors |
title_sort |
estimating distance sampling detection functions when distances are measured with errors |
publishDate |
2010 |
url |
https://risweb.st-andrews.ac.uk/portal/en/researchoutput/estimating-distance-sampling-detection-functions-when-distances-are-measured-with-errors(7cd2ee12-37fb-44d8-9f09-a13f58ab482a).html https://doi.org/10.1007/s13253-010-0021-y http://www.scopus.com/inward/record.url?scp=77949559081&partnerID=8YFLogxK |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Borchers , D , Marques , T , Gunnlaugsson , T & Jupp , P 2010 , ' Estimating distance sampling detection functions when distances are measured with errors ' , Journal of Agricultural, Biological and Environmental Statistics , vol. 15 , no. 3 , pp. 346-361 . https://doi.org/10.1007/s13253-010-0021-y |
op_rights |
info:eu-repo/semantics/restrictedAccess |
op_doi |
https://doi.org/10.1007/s13253-010-0021-y |
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Journal of Agricultural, Biological, and Environmental Statistics |
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15 |
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3 |
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346 |
op_container_end_page |
361 |
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1766040581301075968 |