Age-Groups from Size-Frequency Data: A Versatile and Efficient Method of Analyzing Distribution Mixtures

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Abstract
For estimating age-group parameters from size-frequency data, conventional efficient statistical methods, such as maximum likelihood, can be more effective than the commonly used graphical methods of dissecting a mixed distribution. Fisheries size-frequency data are usually grouped over size intervals and the efficient methods are easily programmed on a computer for this case. Several published alternatives offer no computational advantages over this method. An interactive computer program that assists the user in determining which parameters may be estimated from a set of data is described. The program alternates between constrained direct-search optimization and fast iterative calculations. Two examples of fisheries length-frequency data show that fitting is made easier by employing a subsample aged by biological methods for the preliminary starting values of parameters, and that the best fit may involve a trade-off between statistical precision and biological plausibility. The value of mixture analysis to the fishery worker is to reduce field and laboratory time in the aging of large samples.