2014
DOI: 10.2989/1814232x.2014.897253
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A bootstrap method for estimating bias and variance in statistical fisheries modelling frameworks using highly disparate datasets

Abstract: Statistical models of marine ecosystems use a variety of data sources to estimate parameters using composite or weighted likelihood functions with associated weighting issues and questions on how to obtain variance estimates. Regardless of the method used to obtain point estimates, a method is required for variance estimation. A bootstrap technique is introduced for the evaluation of uncertainty in such models, taking into account inherent spatial and temporal correlations in the datasets, which are commonly t… Show more

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Cited by 13 publications
(4 citation statements)
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“…The sampling distribution for the estimates of sampling efficiency ratio was obtained using nonparametric bootstrapping based on 1,000 samples with replacement (Elvarsson et al. 2014), each of which had the same number of hauls as the original dataset. The median sampling efficiency ratio at a maximum distance of 6.4 km was the estimate for that species.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The sampling distribution for the estimates of sampling efficiency ratio was obtained using nonparametric bootstrapping based on 1,000 samples with replacement (Elvarsson et al. 2014), each of which had the same number of hauls as the original dataset. The median sampling efficiency ratio at a maximum distance of 6.4 km was the estimate for that species.…”
Section: Methodsmentioning
confidence: 99%
“…Sampling efficiencies were reported as the median values for all years and vessel comparisons combined that includes all observations up to a distance of 6.4 km (4 miles; based on asymptotic characteristics of the sampling efficiency ratio estimate; the value of sampling-efficiency ratios did not change when the distance increased past 6.4 km; Figure B2). The sampling distribution for the estimates of sampling efficiency ratio was obtained using nonparametric bootstrapping based on 1,000 samples with replacement (Elvarsson et al 2014), each of which had the same number of hauls as the original dataset. The median sampling efficiency ratio at a maximum distance of 6.4 km was the estimate for that species.…”
Section: Sampling Efficiency Ratiomentioning
confidence: 99%
“…Bootstrap method also applied for measure agglomeration of manufacturing industries at the county level in the United States [6]. In the fishing industry, the application of the bootstrap method has applied to the example of the fish population in Iceland [7]. A bootstrap method for estimating uncertainty of water quality trends for Susquehanna River at Conowingo (U.S.A.) used by [8].…”
Section: Introductionmentioning
confidence: 99%
“…Gadget can be used to assess a single fish stock or to build complex multi-species models. It has been applied in many ecosystems such as the Icelandic continental shelf area for the cod and redfish stocks [7,8,9], the Bay of Biscay in Spain to predict the evolution of the anchovy stock [10], the North East Atlantic to model the porbeagle shark stock [11], or the Barents Sea to model dynamic species interactions [12]. Models developed using the Gadget framework have also been used to provide tactical advice on sustainable exploitation levels of a particular resource.…”
Section: Introductionmentioning
confidence: 99%