Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Anca M. Hanea"'
Publikováno v:
Forecasting, Vol 5, Iss 3, Pp 522-535 (2023)
Mathematical aggregation of probabilistic expert judgments often involves weighted linear combinations of experts’ elicited probability distributions of uncertain quantities. Experts’ weights are commonly derived from calibration experiments base
Externí odkaz:
https://doaj.org/article/8a777ca1ca2d4891bf4bba09b0ed5cea
Publikováno v:
Conservation Science and Practice, Vol 5, Iss 12, Pp n/a-n/a (2023)
Abstract Effective biodiversity conservation requires robust and transparent prioritization of management actions. However, this is often hampered by a lack of spatially‐explicit data on habitat variables and empirical data on the effect of managem
Externí odkaz:
https://doaj.org/article/7f457f33df9d4f5d9833bb467819b2fc
Publikováno v:
Forecasting, Vol 4, Iss 3, Pp 699-716 (2022)
Economic and financial forecasts are important for business planning and government policy but are notoriously challenging. We take advantage of recent advances in individual and group judgement, and a data set of economic and financial forecasts com
Externí odkaz:
https://doaj.org/article/4018c096a1a542beae133ee9e21fa324
Autor:
Bonnie C. Wintle, Eden T. Smith, Martin Bush, Fallon Mody, David P. Wilkinson, Anca M. Hanea, Alexandru Marcoci, Hannah Fraser, Victoria Hemming, Felix Singleton Thorn, Marissa F. McBride, Elliot Gould, Andrew Head, Daniel G. Hamilton, Steven Kambouris, Libby Rumpff, Rink Hoekstra, Mark A. Burgman, Fiona Fidler
Publikováno v:
Royal Society Open Science, Vol 10, Iss 6 (2023)
This paper explores judgements about the replicability of social and behavioural sciences research and what drives those judgements. Using a mixed methods approach, it draws on qualitative and quantitative data elicited from groups using a structured
Externí odkaz:
https://doaj.org/article/76e52f0c4f7f453096d3a9aca4d1c69f
Autor:
Fernando Marmolejo-Ramos, Thomas Workman, Clint Walker, Don Lenihan, Sarah Moulds, Juan C. Correa, Anca M. Hanea, Belona Sonna
Publikováno v:
Discover Artificial Intelligence, Vol 2, Iss 1, Pp 1-16 (2022)
Abstract Algorithms, data, and AI (ADA) technologies permeate most societies worldwide because of their proven benefits in different areas of life. Governments are the entities in charge of harnessing the benefits of ADA technologies above and beyond
Externí odkaz:
https://doaj.org/article/1983b7cff71843f6a4009efd5c609da5
Autor:
Hannah Fraser, Martin Bush, Bonnie C. Wintle, Fallon Mody, Eden T. Smith, Anca M. Hanea, Elliot Gould, Victoria Hemming, Daniel G. Hamilton, Libby Rumpff, David P. Wilkinson, Ross Pearson, Felix Singleton Thorn, Raquel Ashton, Aaron Willcox, Charles T. Gray, Andrew Head, Melissa Ross, Rebecca Groenewegen, Alexandru Marcoci, Ans Vercammen, Timothy H. Parker, Rink Hoekstra, Shinichi Nakagawa, David R. Mandel, Don van Ravenzwaaij, Marissa McBride, Richard O. Sinnott, Peter Vesk, Mark Burgman, Fiona Fidler
Publikováno v:
PLoS ONE, Vol 18, Iss 1 (2023)
As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predicti
Externí odkaz:
https://doaj.org/article/7850340b49dd41b2b3a9522b70b5f30d
Publikováno v:
Entropy, Vol 24, Iss 6, p 757 (2022)
Estimates based on expert judgements of quantities of interest are commonly used to supplement or replace measurements when the latter are too expensive or impossible to obtain. Such estimates are commonly accompanied by information about the uncerta
Externí odkaz:
https://doaj.org/article/cfb0b1b80bbf4bc99d426a4ff779eb55
Autor:
Annemarie Christophersen, Natalia I. Deligne, Anca M. Hanea, Lauriane Chardot, Nicolas Fournier, Willy P. Aspinall
Publikováno v:
Frontiers in Earth Science, Vol 6 (2018)
Bayesian Networks (BNs) are probabilistic graphical models that provide a robust and flexible framework for understanding complex systems. Limited case studies have demonstrated the potential of BNs in modeling multiple data streams for eruption fore
Externí odkaz:
https://doaj.org/article/ff85323cf1de41c3aa71b1148ba20613
Publikováno v:
Risk Analysis. 42:1235-1254
The development and use of probabilistic models, particularly Bayesian networks (BN), to support risk-based decision making is well established. Striking an efficient balance between satisfying model complexity and ease of development requires contin
Autor:
Keith L. McDougall, Ary A. Hoffmann, John W. Morgan, Sonya R. Geange, Rachel A. Slatyer, Adrienne B. Nicotra, Kate D. L. Umbers, James S. Camac, Susanna Venn, Peter A. Vesk, Anca M. Hanea
Publikováno v:
Global Change Biology
Conservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our ca