Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mike Wolosin"'
Autor:
Dave Bell, Sean M. McMahon, Jessica Metcalf, Michelle H. Hersh, Mike Wolosin, James S. Clark, Inés Ibáñez, Luke Pangle, Emily V. Moran, Michael Dietze, Shannon L. LaDeau
Publikováno v:
Oxford Handbooks
This article focuses on the use of Bayesian methods in assessing the probability of rare climate events, and more specifically the potential collapse of the meridional overturning circulation (MOC) in the Atlantic Ocean. It first provides an overview
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c545f95b9d4673617337f807753b701
https://doi.org/10.1093/oxfordhb/9780198703174.013.16
https://doi.org/10.1093/oxfordhb/9780198703174.013.16
Autor:
Pankaj K. Agarwal, Sukhendu Chakraborty, James S. Clark, Inés Ibáñez, Mike Wolosin, Michael Dietze, Shannon L. LaDeau
Publikováno v:
Ecology Letters. 10:647-659
The paradox of biodiversity involves three elements, (i) mathematical models predict that species must differ in specific ways in order to coexist as stable ecological communities, (ii) such differences are difficult to identify, yet (iii) there is w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36a814f47357a0b31362f136fbd9f112
https://doi.org/10.1111/j.1461-0248.2007.01041.x
https://doi.org/10.1111/j.1461-0248.2007.01041.x
Autor:
Hand, David J.1 d.j.hand@imperial.ac.uk
Publikováno v:
International Statistical Review. Dec2010, Vol. 78 Issue 3, p474-475. 2p.
Autor:
Crowder, Martin1 m.crowder@imperial.ac.uk
Publikováno v:
International Statistical Review. Dec2010, Vol. 78 Issue 3, p463-463. 1p.
Autor:
Anthony O' Hagan, Mike West
Bayesian analysis has developed rapidly in applications in the last two decades and research in Bayesian methods remains dynamic and fast-growing. Dramatic advances in modelling concepts and computational technologies now enable routine application o
Autor:
James S. Clark
The environmental sciences are undergoing a revolution in the use of models and data. Facing ecological data sets of unprecedented size and complexity, environmental scientists are struggling to understand and exploit powerful new statistical tools f