Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Edwin J. Green"'
Autor:
Michael R. Gallagher, Nicholas S. Skowronski, Richard G. Lathrop, Timothy McWilliams, Edwin J. Green
Publikováno v:
Canadian Journal of Remote Sensing, Vol 46, Iss 1, Pp 100-111 (2020)
Burn severity maps based on remotely sensed reflectance data provide a useful way for land managers and researchers to represent and compare spatial variation in fire effects among wildfires and prescribed fires. A need exists for an objective and ri
Externí odkaz:
https://doaj.org/article/33cbd3f6532842d89b636282f25682e0
Publikováno v:
Journal of Agronomy and Crop Science. 208:18-27
Autor:
Shidi Wu, Edwin J. Green, Yuanshuo Qu, Phillip L. Vines, Bruce B. Clarke, William A. Meyer, Stacy A. Bonos
Publikováno v:
International Turfgrass Society Research Journal. 14:663-672
Autor:
Edwin J. Green, Michael R. Gallagher, Timothy McWilliams, Nicholas S. Skowronski, Richard G. Lathrop
Publikováno v:
Canadian Journal of Remote Sensing. 46:100-111
Burn severity maps based on remotely sensed reflectance data provide a useful way for land managers and researchers to represent and compare spatial variation in fire effects among wildfires and pr...
Autor:
Paul Bendiks Walberg, Edwin J. Green
Publikováno v:
The American naturalist. 198(5)
The frequency, intensity, and duration of periods of extreme environmental warming are expected to rise over the next hundred years and play an increasing role in species loss resulting from climate change, and yet we know little about their potentia
Autor:
Adam M Wallner, George C Hamilton, Anne L Nielsen, Noel Hahn, Edwin J Green, Cesar R Rodriguez-Saona
Publikováno v:
PLoS ONE, Vol 9, Iss 5, p e95691 (2014)
The brown marmorated stink bug, Halyomorpha halys, a native of Asia, has become a serious invasive pest in the USA. H. halys was first detected in the USA in the mid 1990s, dispersing to over 41 other states. Since 1998, H. halys has spread throughou
Externí odkaz:
https://doaj.org/article/4be1e51025fb45959260fb02c489ea16
Publikováno v:
Introduction to Bayesian Methods in Ecology and Natural Resources ISBN: 9783030607494
Proliferation of spatially indexed data (i.e., variable measurements are associated with a spatial location) has spurred considerable development in statistical modeling. Key texts in this field include Cressie (1993), Cressie and Wikle (2011), Chile
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bc658b90ae150f327857531e7ee51c0
https://doi.org/10.1007/978-3-030-60750-0_8
https://doi.org/10.1007/978-3-030-60750-0_8
Publikováno v:
Introduction to Bayesian Methods in Ecology and Natural Resources ISBN: 9783030607494
Before considering more advanced models which might be used in lieu of standard non-Bayesian approaches such as linear regression or Poisson regression, we start with some relatively simple Bayesian models. These will set the stage for the more sophi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1116f05ef909dcd9d0580fcf12df9b70
https://doi.org/10.1007/978-3-030-60750-0_4
https://doi.org/10.1007/978-3-030-60750-0_4
Publikováno v:
Introduction to Bayesian Methods in Ecology and Natural Resources ISBN: 9783030607494
Selecting a prior distribution is integral to Bayesian analyses. In this chapter, we discuss several approaches to specifying priors. First, we discuss the concept of “noninformative” priors. Next we introduce improper priors. Following this, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c16d403ca564d7d5817d45b372c0ed32
https://doi.org/10.1007/978-3-030-60750-0_3
https://doi.org/10.1007/978-3-030-60750-0_3
Publikováno v:
Introduction to Bayesian Methods in Ecology and Natural Resources ISBN: 9783030607494
Effective Bayesian inference requires familiarity with probability distributions. In fact, as will be seen in subsequent chapters, the most important choices in Bayesian inference usually involve the choices of distributions to represent the state of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8d0e80f1f08de0e3696244fab3bf982
https://doi.org/10.1007/978-3-030-60750-0_2
https://doi.org/10.1007/978-3-030-60750-0_2