Various technical improvements are proposed to the way catch-at-length (CAL) data are treated in fitting the hake assessment model in preparation for finalising the Operating Models for the hake OMP revision. This work has been conducted in collaboration with OLRAC and their code-checking exercise, with near identical results achieved. Results suggest the M. paradoxus resource to be robustly estimated to be at least 10% above BMSY at present for the Reference Case; similar estimates for M. capensis are also above BMSY, though more variable in sensitivity tests.
Reference:
Ross-Gillespie, A., Butterworth, D. 2018-02. Investigating the suitability of the negative log-likelihood term for the catch-at-length data in the hake assessment model.
Ross-Gillespie, A., & Butterworth, D. (2018). Investigating the suitability of the negative log-likelihood term for the catch-at-length data in the hake assessment model ,Faculty of Science ,Department of Mathematics and Applied Mathematics. Retrieved from http://hdl.handle.net/11427/30612
Ross-Gillespie, Andrea, and Doug Butterworth Investigating the suitability of the negative log-likelihood term for the catch-at-length data in the hake assessment model. ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2018. http://hdl.handle.net/11427/30612
Ross-Gillespie A, Butterworth D. Investigating the suitability of the negative log-likelihood term for the catch-at-length data in the hake assessment model. 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/30612
