Exploratory analysis of spatial-temporal patterns in length-frequency data: An example of distributional regression trees

Cleridy E. Lennert-Cody, Mihoko Minami, Patrick K. Tomlinson, Mark N. Maunder

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Understanding the spatial-temporal distributions of fish populations is important for their assessment and management. Given the complex structure often present in fisheries length-frequency samples, there is a need for flexible statistical techniques to explore patterns with these types of data. We present a multivariate regression tree method for binned frequencies that uses the Kullback-Leibler divergence to measure node heterogeneity. To illustrate this approach, we apply the method to length-frequency data for yellowfin tuna caught in the purse-seine fishery of the eastern Pacific Ocean.

Original languageEnglish
Pages (from-to)323-326
Number of pages4
JournalFisheries Research
Volume102
Issue number3
DOIs
Publication statusPublished - 2010 Mar 1

Keywords

  • Kullback-Leibler divergence
  • Length-frequency
  • Multivariate regression tree
  • Yellowfin tuna

ASJC Scopus subject areas

  • Aquatic Science

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