Journal Article10.2307/2348117
Statistics for Spatial Data.
Andrew B. Lawson,Noel A Cressie +1 more
6.5K
About: This article is published in The Statistician. The article was published on 01 Mar 1993. The article focuses on the topics: Spatial analysis.
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Citations
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References
Evaluating the roles of biotransformation, spatial concentration differences, organism home range, and field sampling design on trophic magnification factors.
Jaeshin Kim,Frank A. P. C. Gobas,Jon A. Arnot,David E. Powell,Rita M. Seston,Kent B. Woodburn +5 more
TL;DR: A multibox food-web bioaccumulation model was developed to account for spatial concentration differences and movement of organisms on chemical concentrations in aquatic biota and TMFs and demonstrates that field TMFs are most sensitive to concentration gradients and species migration patterns for substances that are subject to a low degree of biomagnification or trophic dilution.
55
Mapping and uncertainty of predictions based on multiple primary variables from joint co-simulation with Landsat TM image and polynomial regression
TL;DR: In this paper, a remote sensing-aided method for joint mapping and spatial uncertainty analysis of multiple variables correlated with each other is presented. But the method is based on the integration of joint sequential co-simulation with Landsat TM image for mapping and polynomial regression for spatial uncertainty analyses.
54
Persistence of ground-layer bryophytes in a structural retention experiment: initial effects of level and pattern of overstory retention
TL;DR: Declines in species' frequencies and richness were consistently greater in "clear-cut" areas of aggregated treatments than in dispersed retention; liverworts were particularly sensitive to harvest.
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Weight matrices for social influence analysis: An investigation of measurement errors and their effect on model identification and estimation quality
TL;DR: The results suggest that depending on the level of autocorrelation and the topology attributes of the underlying matrix, there is a window of opportunity to identify and model social influence processes even in situations where the ties in a matrix cannot be accurately observed.
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The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach
TL;DR: Investigating HIV/TB mortality determinants and their spatial distribution in the rural Agincourt sub-district for children aged 1–5 years in 2004 found low socio-economic status and maternal deaths impacted indirectly and directly on child mortality, respectively.
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