Suchergebnisse - Inference from spatial processes

oSCR: a spatial capture–recapture R package for inference about spatial ecological processes von Sutherland, Chris, Royle, J. Andrew, Linden, Daniel W.

“… Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture …”
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Two contrasting spatial processes with a common variogram: inference about spatial models from higher-order statistics von Lark, R. M.

“… A key step in geostatistical analysis is the estimation of a variogram function that describes the spatial covariance structure of the variable in question …”
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Inference from spatial processes von Gotway, Carol Anne

“… This gives rise to a wide variety of difficult but fascinating statistical problems. This dissertation considers spatial statistical inference in the areas of estimation, hypothesis testing, and prediction …”
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Data integration for inference about spatial processes: A model-based approach to test and account for data inconsistency von Tenan, Simone, Pedrini, Paolo, Bragalanti, Natalia, Groff, Claudio, Sutherland, Chris

“… , capture-recapture and telemetry). Despite this new methodological focus, the value of opportunistic data for improving inference about spatial ecological processes is unclear and, perhaps more importantly, no procedures are available …”
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On spatial processes and asymptotic inference under near-epoch dependence von Jenish, Nazgul, Prucha, Ingmar R.

“… -mixing process, is shown to be closed under infinite transformations, and thus accommodates models with spatial dynamics …”
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Spatial scale modulates the inference of metacommunity assembly processes von Viana, Duarte S., Chase, Jonathan M.

“… The abundance and distribution of species across the landscape depend on the interaction between local, spatial, and stochastic processes …”
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Lgcp: Inference with spatial and spatio-temporal log-gaussian cox processes in R von Taylor, Benjamin M., Davies, Tilman M., Rowlingson, Barry S., Diggle, Peter J.

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Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation von Vihrs, Ninna, Møller, Jesper, Gelfand, Alan E.

“… In this article, we propose a doubly stochastic spatial point process model with both aggregation and repulsion …”
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Stochastic spatial stream networks for scalable inferences of riverscape processes von Lu, Xinyi, Kaplan, Andee, Kanno, Yoichiro, Valentine, George, Rash, Jacob M., Hooten, Mevin

“… Spatial stream networks (SSN) models characterize correlated ecological processes in dendritic ecosystem …”
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Bayesian inference for finite populations under spatial process settings von Chan‐Golston, Alec M., Banerjee, Sudipto, Handcock, Mark S.

“… Our innovation here is a framework that achieves inference for finite population quantities in spatial process settings …”
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Spatial Causality: A Systematic Review on Spatial Causal Inference von Akbari, Kamal, Winter, Stephan, Tomko, Martin

“… Yet, studies on spatial causal inference are still rare. Causal inference on spatial processes is faced with additional challenges, such as spatial dependency, spatial heterogeneity, and spatial effects …”
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Spatial factor modeling: A Bayesian matrix‐normal approach for misaligned data von Zhang, Lu, Banerjee, Sudipto

“… Multivariate latent spatial process models have proved effective in driving statistical inference and rendering better predictive inference at arbitrary locations for the spatial process. High …”
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Likelihood and Non-parametric Bayesian MCMC Inference for Spatial Point Processes Based on Perfect Simulation and Path Sampling von Berthelsen, Kasper K., Møller, Jesper

“… We consider the combination of path sampling and perfect simulation in the context of both likelihood inference and non-parametric Bayesian inference for pairwise interaction point processes …”
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Optimizing the choice of a spatial weighting matrix in eigenvector-based methods von Bauman, David, Drouet, Thomas, Fortin, Marie-Josée, Dray, Stéphane

“… Eigenvector-mapping methods such as Moran’s eigenvector maps (MEM) are derived from a spatial weighting matrix (SWM …”
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Unifying spatial and social network analysis in disease ecology von Albery, Gregory F., Kirkpatrick, Lucinda, Firth, Josh A., Bansal, Shweta, Farine, Damien

“… Many investigations into sociality and disease may nevertheless be subject to cryptic spatial variation, so ignoring spatial processes can limit inference regarding disease dynamics …”
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Approximate Bayesian inference for large spatial datasets using predictive process models von Eidsvik, Jo, Finley, Andrew O., Banerjee, Sudipto, Rue, Håvard

“… With the increasing availability of geocoded scientific data, hierarchical models involving spatial processes have become a popular method for carrying out spatial inference …”
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Beyond description: the active and effective way to infer processes from spatial patterns von McIntire, Eliot J.B, Fajardo, Alex

“… The ecological processes that create spatial patterns have been examined by direct measurement and through measurement of patterns resulting from experimental manipulations …”
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Inference for Clustered Inhomogeneous Spatial Point Processes von Henrys, P. A., Brown, P. E.

“… We propose a method to test for significant differences in the levels of clustering between two spatial point processes (cases and controls …”
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Including a spatial predictive process in band recovery models improves inference for Lincoln estimates of animal abundance von Gonnerman, Matthew, Linden, Daniel W., Shea, Stephanie A., Sullivan, Kelsey, Kamath, Pauline, Blomberg, Erik

“… Abundance estimation is a critical component of conservation planning, particularly for exploited species where managers set regulations to restrict harvest …”
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Inference for Spatial Processes Using Subsampling: a Simulation Study von Kaiser, Mark S., Hsu, Nan-Jung, Cressie, Noel, Lahiri, Soumendra N.

“… One quantity that captures the empirical distribution of ecological measurements is the spatial cumulative distribution function (SCDF …”
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