Implementing Spatial Data Analysis Software Tools in R

Implementing Exploratory Spatial Data Analysis Methods For..

This paper reports on the development of prototype software designed for exploratory visualization of geographically referenced health statistics. The software prototype provides a number of interactive methods for exploring relationships between risk factors and mortality rates and how they are distributed in space. The use of geographically referenced mortality data to detect disease "hot spo...

Bayesian Prediction in Spatial Data Analysis

Implementing Spatial Segregation Measures in R

Reliable and accurate estimation of residential segregation between population groups is important for understanding the extent of social cohesion and integration in our society. Although there have been considerable methodological advances in the measurement of segregation over the last several decades, the recently developed measures have not been widely used in the literature, in part due to...

Implementing functions for spatial statistical analysis using the R language

is a language similar to for statistical data analysis, based on modern programming concepts and released under the GNU General Public License. It permits the integration of program scripts with compiled dynamically loaded libraries of functions when computing speed is important. Following a broad outline of existing collections of functions for spatial statistics written for , we show how they...

Retinal topography maps in R: new tools for the analysis and visualization of spatial retinal data.

Retinal topography maps are a widely used tool in vision science, neuroscience, and visual ecology, providing an informative visualization of the spatial distribution of cell densities across the retinal hemisphere. Here, we introduce Retina, an R package for computational mapping, inspection of topographic model fits, and generation of average maps. Functions in Retina take cell count data obt...