Regression for overdetermined systems: A fisheries example

L. Manchester, C. A. Field, Andrew McDougall

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)25-39
Number of pages15
JournalCanadian Journal of Statistics
Volume27
Issue number1
DOIs
StatePublished - 1 Jan 1999

Fingerprint

Penalized Least Squares
Overdetermined Systems
Fisheries
Regression
Principal Component Regression
Sea Surface Temperature
Series
Exceed
Predict
Air
Least squares
Observation
Relationships
Temperature
Principal components

Keywords

  • Fisheries recruitment
  • Ill-posed problem
  • North Atlantic cod
  • Overdetermined regression
  • Penalized least squares
  • Principal-components regression

Cite this

Manchester, L. ; Field, C. A. ; McDougall, Andrew. / Regression for overdetermined systems : A fisheries example. In: Canadian Journal of Statistics. 1999 ; Vol. 27, No. 1. pp. 25-39.
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Regression for overdetermined systems : A fisheries example. / Manchester, L.; Field, C. A.; McDougall, Andrew.

In: Canadian Journal of Statistics, Vol. 27, No. 1, 01.01.1999, p. 25-39.

Research output: Contribution to journalArticle

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