Recurrence plot based methods are highly efficient and widely accepted tools for the investigation of time series or one-dimensional data. We present an extension of the recurrence plots and their quantifications in order to study recurrent structures in higher-dimensional spatial data. The capability of this extension is illustrated on prototypical 2D models. Next, the tested and proved approa...

February 19, 2015 Type Package Title Nonparametric spatial data analysis Version 2.0 Date 2013-5-20 Author Daniel McMillen Maintainer Daniel McMillen Description Locally weighted regression, semiparametric and conditionally parametric regression, fourier and cubic spline functions, GMM and linearized spatial logit and probit, k-density functions and counterfactuals, nonp...

This tutorial illustrates the usage of the pRoloc R package for the analysis and interpretation of spatial proteomics data. It walks the reader through the creation of MSnSet instances, that hold the quantitative proteomics data and meta-data and introduces several aspects of data analysis, including data visu-alisation and application of machine learning to predict protein localisation.

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...

Given the above model of stationary random spatial effects { ( ) : } s s R   , our ultimate objective is to apply these concepts to spatial models involving global trends, ( ) s  , i.e., to spatial stochastic models of the form, ( ) ( ) ( ) , Y s s s s R      . In continuous spatial data analysis, the most fully developed models of this type focus on spatial prediction, where values of ...

Given the above formulation of spatial structure in terms of weights matrices, our objective in this section is to develop the basic model of areal-unit dependencies that will be used to capture possible spatial correlations between such units. Unless otherwise stated, we shall implicitly represent the relevant set of areal units, 1 { ,.., } n R R , by their indices, 1,.., i n  . In particular...

The Biodiversity and Ecosystem Informatics Research Agenda (http://bio.gsfc.nasa.gov) notes current inability to compare data across spatial scales as a critical problem: “Biological data from different sources are frequently collected and presented in different scales and resolutions resulting in a loss of detail when multiple data sets are required for data synthesis and analysis.” The propos...

The advancement of GIS data models to allow the eŒective utilization of very large heterogeneous geographic databases requires a new approach that incorporates models of human cognition. The ultimate goal is to provide a cooperative human-computer environment for spatial analysis. We describe the pyramid framework as an example of this new approach within the context of some important aspects o...