Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ...
No abstracts are to be cited without prior reference to the author.Sequential geostatistical simulation methods can be used to calculate empirical confidence intervals for biomass determined from acoustic surveys. Such simulation methods have several advantages: precision can be estimated in the pre...
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ASC 2006 - Theme session I
2024
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ftdatacite:10.17895/ices.pub.25258813 2024-03-31T07:52:01+00:00 Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... Walline, Paul 2024 https://dx.doi.org/10.17895/ices.pub.25258813 https://ices-library.figshare.com/articles/conference_contribution/Sequential_geostatistical_simulation_methods_to_assess_the_error_distribution_function_for_biomass_determined_from_acoustic_survey_data/25258813 unknown ASC 2006 - Theme session I https://ices-library.figshare.com/ICES-ASC-2006/groups ICES Custom Licence https://www.ices.dk/Pages/library_policies.aspx Fisheries and aquaculture Technologies and data Conference contribution article CreativeWork Other 2024 ftdatacite https://doi.org/10.17895/ices.pub.25258813 2024-03-04T14:11:39Z No abstracts are to be cited without prior reference to the author.Sequential geostatistical simulation methods can be used to calculate empirical confidence intervals for biomass determined from acoustic surveys. Such simulation methods have several advantages: precision can be estimated in the presence of autocorrelation and non-random sampling and the combined variance of the acoustic and fish length-frequency measurements can be estimated empirically rather than analytically. In addition, an empirical probability density function (pdf) of the abundance estimate is generated, and can be used, for example, to determine the precision of indices that characterize spatial distribution, such as center of gravity. Examples from the Eastern Bering Sea and the Gulf of Alaska will be presented. The method can be extended to include other sources of uncertainty so that the total error is more closely approximated. A second method for evaluating total uncertainty, consisting of virtual sampling from a known fish ... Conference Object Bering Sea Alaska DataCite Metadata Store (German National Library of Science and Technology) Bering Sea Gulf of Alaska |
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unknown |
topic |
Fisheries and aquaculture Technologies and data |
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Fisheries and aquaculture Technologies and data Walline, Paul Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
topic_facet |
Fisheries and aquaculture Technologies and data |
description |
No abstracts are to be cited without prior reference to the author.Sequential geostatistical simulation methods can be used to calculate empirical confidence intervals for biomass determined from acoustic surveys. Such simulation methods have several advantages: precision can be estimated in the presence of autocorrelation and non-random sampling and the combined variance of the acoustic and fish length-frequency measurements can be estimated empirically rather than analytically. In addition, an empirical probability density function (pdf) of the abundance estimate is generated, and can be used, for example, to determine the precision of indices that characterize spatial distribution, such as center of gravity. Examples from the Eastern Bering Sea and the Gulf of Alaska will be presented. The method can be extended to include other sources of uncertainty so that the total error is more closely approximated. A second method for evaluating total uncertainty, consisting of virtual sampling from a known fish ... |
format |
Conference Object |
author |
Walline, Paul |
author_facet |
Walline, Paul |
author_sort |
Walline, Paul |
title |
Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
title_short |
Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
title_full |
Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
title_fullStr |
Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
title_full_unstemmed |
Sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
title_sort |
sequential geostatistical simulation methods to assess the error distribution function for biomass determined from acoustic survey data ... |
publisher |
ASC 2006 - Theme session I |
publishDate |
2024 |
url |
https://dx.doi.org/10.17895/ices.pub.25258813 https://ices-library.figshare.com/articles/conference_contribution/Sequential_geostatistical_simulation_methods_to_assess_the_error_distribution_function_for_biomass_determined_from_acoustic_survey_data/25258813 |
geographic |
Bering Sea Gulf of Alaska |
geographic_facet |
Bering Sea Gulf of Alaska |
genre |
Bering Sea Alaska |
genre_facet |
Bering Sea Alaska |
op_relation |
https://ices-library.figshare.com/ICES-ASC-2006/groups |
op_rights |
ICES Custom Licence https://www.ices.dk/Pages/library_policies.aspx |
op_doi |
https://doi.org/10.17895/ices.pub.25258813 |
_version_ |
1795030938784104448 |