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Cited by 305

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Dynamic factor analysis to estimate common trends in fisheries time series

Zuur, A F, Tuck, I D, Bailey, N·2003·Canadian Journal of Fisheries and Aquatic Sciences

Abstract

Dynamic factor analysis (DFA) is a technique used to detect common patterns in a set of time series and relationships between these series and explanatory variables. Although DFA is used widely in econometric and psychological fields, it has not been used in fisheries and aquatic sciences to the best of our knowledge. To make the technique more widely accessible, an introductory guide for DFA, at an intermediate level, is presented in this paper. A case study is presented. The analysis of 13 landings-per-unit-effort series for Nephrops around northern Europe identified three common trends for 12 of the series, with one series being poorly fitted, but no relationships with the North Atlantic Oscillation (NAO) or sea surface temperature were found. The 12 series could be divided into six groups based on factor loadings from the three trends.

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Metadata

Authors
Zuur, A. F., Tuck, I. D., & Bailey, N.
Venue
Canadian Journal of Fisheries and Aquatic Sciences
Published
2003-05-01
Volume
60
Issue
5
Pages
542-552
ISSN
  • 0706-652X (ISSN-L)
  • 1205-7533
OpenAlex
W2150186167
Cited by
305
References
26
FWCI
5.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Dynamic factor analysis to estimate common trends in fisheries time series. https://app.cochat.ai/papers/10.1139/f03-030
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Zuur, A. F., Tuck, I. D., & Bailey, N. (2003). Dynamic factor analysis to estimate common trends in fisheries time series. Canadian Journal of Fisheries and Aquatic Sciences. https://doi.org/10.1139/f03-030

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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