Title :
Merging aggregate catch data with uncertain prior knowledge to approximate age and size distributions and selectivity functions
Author_Institution :
Center for Quantitative Sci. in Fisheries, Washington Univ., Seattle, WA, USA
Abstract :
The problem of determining fish age and size distributions and gear selectivity from aggregate data is approached as an ill-posed inverse problem. Minimum cross-entropy inversion techniques allow the selection of a reasonable unique solution, directly incorporating background information of uncertain quality
Keywords :
aquaculture; information theory; operations research; probability; age distribution; aquaculture; fishery; ill-posed inverse problem; minimum cross-entropy inversion; probability; selectivity functions; size distributions; uncertain quality; Aggregates; Aging; Aquaculture; Biological system modeling; Biomass; Costs; Gears; Marine animals; Merging; Sampling methods;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
