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DOI: 10.1371/journal.pone.0141697
论文题名:
Characterising Uncertainty in Expert Assessments: Encoding Heavily Skewed Judgements
作者: Rebecca A. O’Leary; Samantha Low-Choy; Rebecca Fisher; Kerrie Mengersen; M. Julian Caley
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2015
发表日期: 2015-10-30
卷: 10, 期:10
语种: 英语
英文关键词: Skewness ; Normal distribution ; Statistical distributions ; Taxonomy ; Probability distribution ; Species diversity ; Coral reefs ; Software tools
英文摘要: When limited or no observed data are available, it is often useful to obtain expert knowledge about parameters of interest, including point estimates and the uncertainty around these values. However, it is vital to elicit this information appropriately in order to obtain valid estimates. This is particularly important when the experts’ uncertainty about these estimates is strongly skewed, for instance when their best estimate is the same as the lowest value they consider possible. Also this is important when interest is in the aggregation of elicited values. In this paper, we compare alternative distributions for describing such estimates. The distributions considered include the lognormal, mirror lognormal, Normal and scaled Beta. The case study presented here involves estimation of the number of species in coral reefs, which requires eliciting counts within broader taxonomic groups, with highly skewed uncertainty estimates. This paper shows substantial gain in using the scaled Beta distribution, compared with Normal or lognormal distributions. We demonstrate that, for this case study on counting species, applying the novel encoding methodology developed in this paper can facilitate the acquisition of more rigorous estimates of (hierarchical) count data and credible bounds. The approach can also be applied to the more general case of enumerating a sampling frame via elicitation.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0141697&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/21778
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Australian Institute of Marine Science, The UWA Oceans Institute (M096), 35 Stirling Highway, Crawley, Western Australia 6009, Australia;School of Mathematical Sciences, Science and Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland 4001, Australia;Australian Institute of Marine Science, The UWA Oceans Institute (M096), 35 Stirling Highway, Crawley, Western Australia 6009, Australia;School of Mathematical Sciences, Science and Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland 4001, Australia;Australian Institute of Marine Science, PMB 3 Townsville MC, Townsville, Queensland 4810, Australia

Recommended Citation:
Rebecca A. O’Leary,Samantha Low-Choy,Rebecca Fisher,et al. Characterising Uncertainty in Expert Assessments: Encoding Heavily Skewed Judgements[J]. PLOS ONE,2015-01-01,10(10)
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