Regression for overdetermined systems: A fisheries example
Abstract In trying to establish the relationship between a yearly fisheries recruitment series and meteorological or oceanographic variables such as air pressure or sea surface temperature, we are often faced with the situation where the number of regressors exceeds the number of observations. In th...
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crwiley:10.2307/3315488 2023-12-03T10:18:59+01:00 Regression for overdetermined systems: A fisheries example Manchester, L. Field, C. A. Mcdougall, A. 1999 http://dx.doi.org/10.2307/3315488 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.2307%2F3315488 https://onlinelibrary.wiley.com/doi/pdf/10.2307/3315488 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Canadian Journal of Statistics volume 27, issue 1, page 25-39 ISSN 0319-5724 1708-945X Statistics, Probability and Uncertainty Statistics and Probability journal-article 1999 crwiley https://doi.org/10.2307/3315488 2023-11-09T13:54:39Z Abstract In trying to establish the relationship between a yearly fisheries recruitment series and meteorological or oceanographic variables such as air pressure or sea surface temperature, we are often faced with the situation where the number of regressors exceeds the number of observations. In this paper we use the techniques of penalized least squares and principal‐components regression to determine whether air pressure over the North Atlantic can be used to predict two North Atlantic cod recruitment series. The results suggest that penalized least squares can be very effective in these situations. Article in Journal/Newspaper atlantic cod North Atlantic Wiley Online Library (via Crossref) Canadian Journal of Statistics 27 1 25 39 |
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Open Polar |
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Wiley Online Library (via Crossref) |
op_collection_id |
crwiley |
language |
English |
topic |
Statistics, Probability and Uncertainty Statistics and Probability |
spellingShingle |
Statistics, Probability and Uncertainty Statistics and Probability Manchester, L. Field, C. A. Mcdougall, A. Regression for overdetermined systems: A fisheries example |
topic_facet |
Statistics, Probability and Uncertainty Statistics and Probability |
description |
Abstract In trying to establish the relationship between a yearly fisheries recruitment series and meteorological or oceanographic variables such as air pressure or sea surface temperature, we are often faced with the situation where the number of regressors exceeds the number of observations. In this paper we use the techniques of penalized least squares and principal‐components regression to determine whether air pressure over the North Atlantic can be used to predict two North Atlantic cod recruitment series. The results suggest that penalized least squares can be very effective in these situations. |
format |
Article in Journal/Newspaper |
author |
Manchester, L. Field, C. A. Mcdougall, A. |
author_facet |
Manchester, L. Field, C. A. Mcdougall, A. |
author_sort |
Manchester, L. |
title |
Regression for overdetermined systems: A fisheries example |
title_short |
Regression for overdetermined systems: A fisheries example |
title_full |
Regression for overdetermined systems: A fisheries example |
title_fullStr |
Regression for overdetermined systems: A fisheries example |
title_full_unstemmed |
Regression for overdetermined systems: A fisheries example |
title_sort |
regression for overdetermined systems: a fisheries example |
publisher |
Wiley |
publishDate |
1999 |
url |
http://dx.doi.org/10.2307/3315488 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.2307%2F3315488 https://onlinelibrary.wiley.com/doi/pdf/10.2307/3315488 |
genre |
atlantic cod North Atlantic |
genre_facet |
atlantic cod North Atlantic |
op_source |
Canadian Journal of Statistics volume 27, issue 1, page 25-39 ISSN 0319-5724 1708-945X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.2307/3315488 |
container_title |
Canadian Journal of Statistics |
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27 |
container_issue |
1 |
container_start_page |
25 |
op_container_end_page |
39 |
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1784266111895732224 |