Detecting sampling outliers and sampling heterogeneity when catch-at-length is estimated using the ratio estimator
Author(s) -
J. Vigneau,
Stéphanie Mahévas
Publication year - 2007
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsm077
Subject(s) - sampling (signal processing) , estimator , outlier , groundfish , statistics , fish stock , computer science , econometrics , sampling design , stock assessment , fishing , stock (firearms) , data mining , fishery , mathematics , fisheries management , geography , biology , population , demography , archaeology , filter (signal processing) , sociology , computer vision
Measuring fish on board fishing vessels or at fish markets to collect data for stock assessment purposes is one of the most straightforward actions carried out by fisheries scientists worldwide. However, such samples are not straightforward to handle and analyse because of their vector-type structure. A generic tool that allows investigation in any multinomial-like sampling scheme is provided, as long as the scheme is built on a ratio estimator, which is the case for most length sampling in the fisheries sector. The use of this tool is discussed using data obtained from two different sampling designs, one consisting of commercial market samples by category and the other on fishing activity or metier. The identification of outliers, misallocated samples, or potential bias as well as the analysis of heterogeneity within and between strata are discussed. The objective of such exploratory analyses is to help sampling coordinators design the best sampling scheme and improve the quality of input data for stock assessment models. The statistics described here are easy to implement and their use is recommended as a necessary stage before any use of sampling data at an international level.
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