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Determining optimal neighborhood size for ecological studies using leave-one-out cross validation

We employed a leave-one-out cross validation to determine optimally sized neighborhood. Variations between a single point and the other points within each filter size for all the points in the study area were evaluated, and the mean squared error (MSE) for each filter was calculated. The filter with...

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Detalles Bibliográficos
Autores principales: Kim, Deok Ryun, Ali, Mohammad, Sur, Dipika, Khatib, Ahmed, Wierzba, Thomas F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361501/
https://www.ncbi.nlm.nih.gov/pubmed/22471893
http://dx.doi.org/10.1186/1476-072X-11-10
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author Kim, Deok Ryun
Ali, Mohammad
Sur, Dipika
Khatib, Ahmed
Wierzba, Thomas F
author_facet Kim, Deok Ryun
Ali, Mohammad
Sur, Dipika
Khatib, Ahmed
Wierzba, Thomas F
author_sort Kim, Deok Ryun
collection PubMed
description We employed a leave-one-out cross validation to determine optimally sized neighborhood. Variations between a single point and the other points within each filter size for all the points in the study area were evaluated, and the mean squared error (MSE) for each filter was calculated. The filter with the lowest MSE was considered as the optimal neighborhood. The method is useful in determining the optimal neighborhood for both geographic and population filters.
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spelling pubmed-33615012012-06-01 Determining optimal neighborhood size for ecological studies using leave-one-out cross validation Kim, Deok Ryun Ali, Mohammad Sur, Dipika Khatib, Ahmed Wierzba, Thomas F Int J Health Geogr Methodology We employed a leave-one-out cross validation to determine optimally sized neighborhood. Variations between a single point and the other points within each filter size for all the points in the study area were evaluated, and the mean squared error (MSE) for each filter was calculated. The filter with the lowest MSE was considered as the optimal neighborhood. The method is useful in determining the optimal neighborhood for both geographic and population filters. BioMed Central 2012-04-03 /pmc/articles/PMC3361501/ /pubmed/22471893 http://dx.doi.org/10.1186/1476-072X-11-10 Text en Copyright ©2012 Kim et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Kim, Deok Ryun
Ali, Mohammad
Sur, Dipika
Khatib, Ahmed
Wierzba, Thomas F
Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
title Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
title_full Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
title_fullStr Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
title_full_unstemmed Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
title_short Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
title_sort determining optimal neighborhood size for ecological studies using leave-one-out cross validation
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361501/
https://www.ncbi.nlm.nih.gov/pubmed/22471893
http://dx.doi.org/10.1186/1476-072X-11-10
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