Journal ArticleDOI
A Variance-Stabilizing Coding Scheme for Spatial Link Matrices:
Reads0
Chats0
TLDR
In the new S-coding scheme the topology induced heterogeneity can be removed in toto for Moran's I as well as for moving average processes and it can be substantially alleviated for autoregressive processes.Abstract:
In spatial statistics and spatial econometrics two coding schemes are used predominately. Except for some initial work, the properties of both coding schemes have not been investigated systematically. In this paper we do so for significant spatial processes specified as either a simulta-neous autoregressive or a moving average process. Results show that the C-coding scheme emphasizes spatial objects with relatively large numbers of connections, such as those in the interior of a study region. In contrast, the W-coding scheme assigns higher leverage to spatial objects with few connections, such as those on the periphery of a study region. To address this topology-induced heterogeneity, we design a novel S-coding scheme whose properties lie in between those of the C-coding and the W-coding schemes. To compare these three coding schemes within and across the different spatial processes, we find a set of autocorrelation parameters that makes the processes stochastically homologous via a method based on the ex...read more
Citations
More filters
Journal ArticleDOI
Methods to account for spatial autocorrelation in the analysis of species distributional data : a review
Carsten F. Dormann,Jana M. McPherson,Miguel B. Araújo,Roger Bivand,Janine Bolliger,Gudrun Carl,Richard G. Davies,Alexandre H. Hirzel,Walter Jetz,W. Daniel Kissling,Ingolf Kühn,Ralf Ohlemüller,Pedro R. Peres-Neto,Björn Reineking,Boris Schröder,Frank M. Schurr,Robert J. Wilson +16 more
TL;DR: In this paper, the authors describe six different statistical approaches to infer correlates of species distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations.
Journal ArticleDOI
Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM)
TL;DR: The Principal Coordinates of Neighbors of Neighbor Matrices (PCNM) approach as discussed by the authors was proposed to create spatial predictors that can be easily incorporated into regression or canonical analysis models, providing a flexible tool especially when contrasted to the family of autoregressive models and trend surface analysis which are of common use in ecological and geographical analysis.
Journal ArticleDOI
Spatial autocorrelation and the selection of simultaneous autoregressive models
W. Daniel Kissling,Gudrun Carl +1 more
TL;DR: In this article, the performance of three different simultaneous autoregressive (SAR) model types (spatial error = SAR err, lagged = SAR lag and mixed = SAR mix ) and common ordinary least squares (OLS) regression when accounting for spatial autocorrelation in species distribution data using four artificial data sets with known (but different) spatial auto-correlation structures.
Journal ArticleDOI
Constructing the Spatial Weights Matrix Using a Local Statistic
Arthur Getis,Jared Aldstadt +1 more
TL;DR: The two-variable local statistics model (LSM) as discussed by the authors is based on the G i * local statistic, defined as the critical distance beyond which no discernible increase in clustering of high or low values exists.
Journal ArticleDOI
Computing the Jacobian in Gaussian Spatial Autoregressive Models: An Illustrated Comparison of Available Methods
TL;DR: This is the accepted version of the following article:Computing the Jacobian in Gaussian Spatial Autoregressive Models: An Illustrated Comparison of Available Methods, Geographical Analysis 2013, 45(2):150-179, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.12008/abstract.
References
More filters
Journal ArticleDOI
Local Indicators of Spatial Association—LISA
TL;DR: In this paper, a new general class of local indicators of spatial association (LISA) is proposed, which allow for the decomposition of global indicators, such as Moran's I, into the contribution of each observation.
Book
Spatial Econometrics: Methods and Models
TL;DR: In this article, a typology of Spatial Econometric Models is presented, and the maximum likelihood approach to estimate and test Spatial Process Models is proposed, as well as alternative approaches to Inference in Spatial process models.
Journal ArticleDOI
Local Spatial Autocorrelation Statistics: Distributional Issues and an Application
J. K. Ord,Arthur Getis +1 more
TL;DR: In this paper, the statistics Gi(d) and Gi*(d), introduced in Getis and Ord (1992) for the study of local pattern in spatial data, are extended and their properties further explored.
Journal ArticleDOI
Estimation Methods for Models of Spatial Interaction
TL;DR: In this paper, a simplified computational scheme is given and extended to mixed regressive-autoregressive models for spatial interaction, and the ML estimator is compared with several alternatives.