SSN: AnRPackage for Spatial Statistical Modeling on Stream Networks

SSN: An R Package for Spatial Statistical Modeling on Stream Networks

The SSN package for R provides a set of functions for modeling stream network data. The package can import geographic information systems data or simulate new data as a ‘SpatialStreamNetwork’, a new object class that builds on the spatial sp classes. Functions are provided that fit spatial linear models (SLMs) for the ‘SpatialStreamNetwork’ object. The covariance matrix of the SLMs use distance...

Statistical Modeling of Spatial Extremes

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. This article reviews recent progress in the statistical modeling of spatial extremes, starting with sketches of the necessary elements of extreme value statistics and geostatistics. The...

Spatial Statistical Modeling in Biology

Asp–ssn: an Effective Approach for Linking Semantic Social Networks

The dramatic increase of social networking sites forced web users to duplicate their identity on many of them. But, the lack of interoperability and linkage between these social networks allowed users’ information to be disseminated within walled garden data islands. Achieving interoperability will contribute to the creation of rich knowledge base that can be used for querying social networks a...

Spatial multivariate design in the plane and on stream networks

In environmental studies, measurements of interest are often taken on multiple variables. The results of spatial data analyses can be substantially affected by the spatial configuration of the sites where measurements are taken. Hence, optimal designs which result in data guaranteeing efficient statistical inferences need to be studied. We study optimal designs on two large classes of spatial r...