Do Different Methods Provide Accurate Probability Statements in the Short Term?
Restrepo, V. R.; Patterson, K. R.; Darby, Chris; Gavaris, S.; Kell, Laurence T.; Lewy, P.; Mesnil, Benoit; Punt, A. E.; Cook, R. M.; O’Brien, C. M.; Skagen, Dankert W.; Stefánsson, Gunnar
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http://hdl.handle.net/11250/100457Utgivelsesdato
2000Metadata
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The performance of uncertainty estimation procedures was evaluated with respect to
accuracy. A confidence statement is said to be accurate if the confidence point achieves the
desired probability coverage. A Monte Carlo experiment with 100 trials was conducted with a
true population that experienced contrast between low and high fishing mortality.
Observations for the last 25 years were drawn stochastically by adding measurement error. The
assessment approaches were VPA-based (ADAPT and XSA with errors on the effort data). The
Delta Method , parametric bootstrap and non-parametric bootstrap (NPB), and a Bayesian
approach were used to quantify coverage and assess the accuracy of confidence limits of
estimated interest parameters (F0.1, SSB and TACF0.1 in year 26) by comparing against the true
values. Variations of the Delta Method and bootstrap were used to account for statistical
estimation bias. The results indicated that accurate inference statements are possible with the
different approaches and that bias correction can improve accuracy when it can be applied. The
bias-corrected Delta-ADAPT and bias-corrected NPB-ADAPT applications performed best.
Inference statements about F0.1 were more accurate than those for SSB or TAC.
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ICES CM documents2000/V:08