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...
Published in: | Canadian Journal of Statistics |
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Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
1999
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Subjects: | |
Online Access: | 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 |
Summary: | 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. |
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