Results 1 to 10 of about 324,057 (86)

Inference for spatial processes using imperfect data from measurements and numerical simulations [PDF]

, 2016
We present a framework for inference for spatial processes that have actual values imperfectly represented by data. Environmental processes represented as spatial fields, either at fixed time points, or aggregated over fixed time periods, are studied.
Youngman, BD, Stephenson, DB
core   +4 more sources

Inferring Colonization Processes from Population Dynamics in Spatially Structured Predator-Prey Systems [PDF]

Ecology, 2000
We examine how spatial subdivision of predator–prey systems affects colonization processes in metapopulations. Dynamics of the herbivorous spider mite Tetranychus urticae (prey) and the predatory mite Phytoseiulus persimilis are highly unstable on isolated bean plants (Phaseolus lunatus) and ultimately result in extinction of prey and predators ...
McCauley, E., Kendall, B.E., Janssen, A., Wood, S., Murdoch, W.W., Hosseini, P., Briggs, C.J., Ellner, S.P., Nisbet, R.M., Sabelis, M.W., Turchin, P.   +10 more
openaire   +3 more sources

Likelihood-based inference for max-stable processes [PDF]

, 2009
The last decade has seen max-stable processes emerge as a common tool for the statistical modeling of spatial extremes. However, their application is complicated due to the unavailability of the multivariate density function, and so likelihood-based ...
Padoan, Simone A., Ribatet, Mathieu, Sisson, Scott A.   +2 more
core   +6 more sources

INLA or MCMC? A Tutorial and Comparative Evaluation for Spatial Prediction in log-Gaussian Cox Processes [PDF]

, 2012
We investigate two options for performing Bayesian inference on spatial log-Gaussian Cox processes assuming a spatially continuous latent field: Markov chain Monte Carlo (MCMC) and the integrated nested Laplace approximation (INLA). We first describe the
Diggle, Peter J., Taylor, Benjamin M.
core   +1 more source

Probability as a physical motive [PDF]

, 2007
Recent theoretical progress in nonequilibrium thermodynamics, linking the physical principle of Maximum Entropy Production ("MEP") to the information-theoretical "MaxEnt" principle of scientific inference, together with conjectures from theoretical ...
Brooks, Denbigh, Eddington, Ehrenfest, Einstein, Feynman, Gibbs, Hofstadter, Johnstone, Kauffman, Lasota, Lovelock, Monod, Penrose, Peter Martin, Prigogine, Prigogine, Prigogine, Salthe, Schneider, Schrödinger, Spencer-Brown, Wicken   +22 more
core   +4 more sources

Factors controlling the regeneration process in unevenly aged silver fir forests: inferences from the spatial pattern of trees [PDF]

Journal of Forest Science, 2006
The main objective of this study was to prove the relationship between the spatial pattern of trees and distribution of advanced regeneration in structured Abies alba Mill. forests in the Western Carpathians (of southern Poland). In 13 sample plots (0.45-1.00 ha in size), the locations of all live trees above 15 cm in d1.3 and all stumps of canopy ...
openaire   +2 more sources

Inferring Processes from Spatial Patterns: The Role of Directional and Non–Directional Forces in Shaping Fish Larvae Distribution in a Freshwater Lake System

PLoS ONE, 2012
Larval dispersal is a crucial factor for fish recruitment. For fishes with relatively small-bodied larvae, drift has the potential to play a more important role than active habitat selection in determining larval dispersal; therefore, we expect small-bodied fish larvae to be poorly associated with habitat characteristics.
Andrea Bertolo, F Guillaume Blanchet, Pierre Magnan, Philippe Brodeur, Marc Mingelbier, Pierre Legendre   +5 more
openaire   +4 more sources

Statistical Modeling of Spatial Extremes [PDF]

, 2012
The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection.
Davison, A. C., Padoan, S. A., Ribatet, M.   +2 more
core   +7 more sources

Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster [PDF]

, 2010
Background: Reaction-diffusion systems are frequently used in systems biology to model developmental and signalling processes. In many applications, count numbers of the diffusing molecular species are very low, leading to the need to explicitly model ...
Dewar, M.A., Kadirkamanathan, V., Opper, M., Sanguinetti, G.   +3 more
core   +4 more sources

Hierarchical Bayesian auto-regressive models for large space time data with applications to ozone concentration modelling [PDF]

, 2012
Increasingly large volumes of space-time data are collected everywhere by mobile computing applications, and in many of these cases temporal data are obtained by registering events, for example telecommunication or web traffic data.
Banerjee, Banerjee, Berrocal, Carroll, Cocchi, Cressie, Cressie, Cressie, Cressie, Daniels, Fields Development Team, Finley, Finley, Franklin, Gelfand, Gelfand, Gelfand, Gelman, Gelman, Gilleland, Guttorp, Haas, Hartman, Huang, Huang, Huerta, Jammalamadaka, Johannesson, Johannesson, Kammann, Little, Liu, McMillan, McMillan, Nobre, Nychka, Paciorek, Reich, Rue, Sahu, Sahu, Sahu, Sahu, Spiegelhalter, Stein, Stein, Stein, Thompson, Zhang   +48 more
core   +1 more source