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Spatial Independence (spatial + independence)

Distribution by Scientific Domains

Mathematics and Statistics	50%

Selected Abstracts

Testing the boolean hypothesis in the non-convex case when a bounded grain can be assumed

ENVIRONMETRICS, Issue 2 2008
J. Chad
Abstract Spatial independence of objects is a strong hypothesis when using boolean models. Methods to test it have then been developed, but only when the objects are convex. We propose here to replace this assumption by a bound assumption of the objects which can be more easily assumed when modeling spatial patterns in ecology and agricultural science. A test is then proposed, based on the length of the voids of the intersection between transect lines and a dilation of the original process related to the bound value. Its application is shown to several examples, together with its extension to an epidemiological case on orchards, where this problem comes from. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Bayesian Spatial Survival Models for Political Event Processes

AMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 1 2009
David Darmofal
Research in political science is increasingly, but independently, modeling heterogeneity and spatial dependence. This article draws together these two research agendas via spatial random effects survival models. In contrast to standard survival models, which assume spatial independence, spatial survival models allow for spatial autocorrelation at neighboring locations. I examine spatial dependence in both semiparametric Cox and parametric Weibull models and in both individual and shared frailty models. I employ a Bayesian approach in which spatial autocorrelation in unmeasured risk factors across neighboring units is incorporated via a conditionally autoregressive (CAR) prior. I apply the Bayesian spatial survival modeling approach to the timing of U.S. House members' position announcements on NAFTA. I find that spatial shared frailty models outperform standard nonfrailty models and nonspatial frailty models in both the semiparametric and parametric analyses. The modeling of spatial dependence also produces changes in the effects of substantive covariates in the analysis. [source]

What helps Opuntia stricta invade Kruger National Park, South Africa: Baboons or elephants?

APPLIED VEGETATION SCIENCE, Issue 2 2007
L.C. Foxcroft
Germishuizen & Meyer (2003) for plant species Abstract Question: Is Opuntia stricta more frequent, and its patches larger, under trees suitable for baboon roosting? If so, does it mean that baboons are major dispersal agents and that plants established under these trees are important foci of Opuntia stricta spread? Location: Skukuza, Kruger National Park, South Africa. Method: We surveyed an area invaded by Opuntia stricta in the Skukuza region of KNP. The survey included plots under potential baboon roosting trees,plots under trees unlikely to support baboons,and paired randomly located open sites. Results: The null hypothesis -tree- Opuntia spatial independence , can be rejected for Acacia nilotica, but not for Spirostachys africana. Opuntia plants are positively associated with Acacia trees suitable for baboon roosting. However, there is no significant difference between frequency of Opuntia under Acacia trees suitable and unsuitable for baboon roosting. It appears that all Acacia trees can serve as nurse trees for Opuntia. Compared to plots under Acacia trees, frequencies of old and robust Opuntia plants are significantly higher in open areas and under dead trees. Conclusions: While baboons may be responsible for long distance Opuntia dispersal (over km),their role is not detectable at a local scale. On the other hand, elephants seem to contribute substantially to the local vegetative propagation of this species. Opuntia establishment and growth are more influenced by micro-habitat than previously thought. [source]

Nonparametric One-way Analysis of Variance of Replicated Bivariate Spatial Point Patterns

BIOMETRICAL JOURNAL, Issue 1 2004
Sabine Landau
Abstract A common problem in neuropathological studies is to assess the spatial patterning of cells on tissue sections and to compare spatial patterning between disorder groups. For a single cell type, the cell positions constitute a univariate point process and interest focuses on the degree of spatial aggregation. For two different cell types, the cell positions constitute a bivariate point process and the degree of spatial interaction between the cell types is of interest. We discuss the problem of analysing univariate and bivariate spatial point patterns in the one-way design where cell patterns have been obtained for groups of subjects. A bootstrapping procedure to perform a nonparametric one-way analysis of variance of the spatial aggregation of a univariate point process has been suggested by Diggle, Lange and Bene, (1991). We extend their replication-based approach to allow the comparison of the spatial interaction of two cell types between groups, to include planned comparisons (contrasts) and to assess whole groups against complete spatial randomness and spatial independence. We also accommodate several replicate tissue sections per subject. An advantage of our approach is that it can be applied when processes are not stationary, a common problem in brain tissue sections since neurons are arranged in cortical layers. We illustrate our methods by applying them to a neuropathological study to investigate abnormalities in the functional relationship between neurons and astrocytes in HIV associated dementia. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]