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 language | English |
|---|---|
| Pages (from-to) | 323-326 |
| Number of pages | 4 |
| Journal | Fisheries Research |
| Volume | 102 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2010 Mar |
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Keywords
- Kullback-Leibler divergence
- Length-frequency
- Multivariate regression tree
- Yellowfin tuna
ASJC Scopus subject areas
- Aquatic Science
Cite this
Exploratory analysis of spatial-temporal patterns in length-frequency data : An example of distributional regression trees. / Lennert-Cody, Cleridy E.; Minami, Mihoko; Tomlinson, Patrick K.; Maunder, Mark N.
In: Fisheries Research, Vol. 102, No. 3, 03.2010, p. 323-326.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Exploratory analysis of spatial-temporal patterns in length-frequency data
T2 - An example of distributional regression trees
AU - Lennert-Cody, Cleridy E.
AU - Minami, Mihoko
AU - Tomlinson, Patrick K.
AU - Maunder, Mark N.
PY - 2010/3
Y1 - 2010/3
N2 - 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.
AB - 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.
KW - Kullback-Leibler divergence
KW - Length-frequency
KW - Multivariate regression tree
KW - Yellowfin tuna
UR - http://www.scopus.com/inward/record.url?scp=76849104050&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=76849104050&partnerID=8YFLogxK
U2 - 10.1016/j.fishres.2009.11.014
DO - 10.1016/j.fishres.2009.11.014
M3 - Article
AN - SCOPUS:76849104050
VL - 102
SP - 323
EP - 326
JO - Fisheries Research
JF - Fisheries Research
SN - 0165-7836
IS - 3
ER -