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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Bibliographic Details
Published in:Canadian Journal of Statistics
Main Authors: Manchester, L., Field, C. A., Mcdougall, A.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 1999
Subjects:
Statistics, Probability and Uncertainty
Statistics and Probability
atlantic cod
North Atlantic
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
Description
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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