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- W2108293798 abstract "An exploited stock's length distribution over a set of fixed length intervals can be represented as the product of its age distribution vector and a matrix whose columns are the length distributions of the various age-groups. This matrix should be reasonably stable over time, so it can be estimated from age–length sampling done at any time. Then, so long as the number of length intervals exceeds the number of age-groups, a restricted least-squares estimate of the age distribution underlying any sample length distribution can be found with certainty by quadratic programming. For practical work, the advantages of this method over numerical and closed-form alternatives are that the estimates are reproducible and never contain any negative values. A general statistical treatment is impossible owing to the exclusion of negative values and the presence of sampling error in the matrix of estimated age-specific length distributions, but simulation trials show that in commercial fishery assessments least-squares estimates can be obtained that are unbiased and nearly as precise as maximum-likelihood estimates.Key words: age composition, age–length key, linear regression, restricted least-squares, quadratic programming, simulation" @default.
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- W2108293798 date "1981-03-01" @default.
- W2108293798 modified "2023-09-25" @default.
- W2108293798 title "Restricted Least-Squares Estimates of Age Composition from Length Composition" @default.
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- W2108293798 doi "https://doi.org/10.1139/f81-041" @default.
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