Eigenvector Spatial Filtering and Lasso

Eigenvector Spatial Filtering and Lasso PDF Author: Rowan Cherodian
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description

Eigenvector Spatial Filtering and Lasso

Eigenvector Spatial Filtering and Lasso PDF Author: Rowan Cherodian
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description


Application of Lasso to the Eigenvector Selection Problem in Eigenvector Based Spatial Filtering

Application of Lasso to the Eigenvector Selection Problem in Eigenvector Based Spatial Filtering PDF Author: Hajime Seya
Publisher:
ISBN:
Category :
Languages : en
Pages : 27

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Book Description
Eigenvector based spatial filtering is one of the well-used approaches to model spatial autocorrelation among the observations or errors in a regression model. In this approach, subset of eigenvectors extracted from a modified spatial weight matrix is added to the model as explanatory variables. The subset is typically specified via the forward stepwise model selection procedure, but it is disappointingly slow when the number of observations n takes a large number. Hence as a complement or alternative, the present paper proposes the use of the LASSO (L1-penalized regression) to select the eigenvectors. The LASSO model selection procedure is applied to the well-known Boston housing dataset and simulation dataset, and its performance is compared with that of the stepwise procedure. The obtained results suggest that the LASSO is fairly fast compared the stepwise procedure, and can select eigenvectors effectively even if dataset is relatively large (n = 10000), to which the forward stepwise procedure is uneasy to apply.

Advanced Introduction to Spatial Statistics

Advanced Introduction to Spatial Statistics PDF Author: Griffith, Daniel A.
Publisher: Edward Elgar Publishing
ISBN: 1800372825
Category : Social Science
Languages : en
Pages : 125

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Book Description
This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.

Spatial Spectrum Estimation by Eigenvector Methods

Spatial Spectrum Estimation by Eigenvector Methods PDF Author: Chang-Guo Zhou
Publisher:
ISBN:
Category :
Languages : en
Pages : 258

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Book Description


Spatial Autocorrelation and Spatial Filtering

Spatial Autocorrelation and Spatial Filtering PDF Author: Daniel A. Griffith
Publisher: Springer Science & Business Media
ISBN: 3540248064
Category : Science
Languages : en
Pages : 261

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Book Description
Scientific visualization may be defined as the transformation of numerical scientific data into informative graphical displays. The text introduces a nonverbal model to subdisciplines that until now has mostly employed mathematical or verbal-conceptual models. The focus is on how scientific visualization can help revolutionize the manner in which the tendencies for (dis)similar numerical values to cluster together in location on a map are explored and analyzed. In doing so, the concept known as spatial autocorrelation - which characterizes these tendencies - is further demystified.

Spatial Autocorrelation and Spatial Filtering

Spatial Autocorrelation and Spatial Filtering PDF Author: Daniel A. Griffith
Publisher:
ISBN: 9783642534836
Category :
Languages : en
Pages : 268

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Book Description


Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering PDF Author: Daniel Griffith
Publisher: Academic Press
ISBN: 0128156929
Category : Business & Economics
Languages : en
Pages : 286

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Book Description
Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre. Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models Includes computer code and template datasets for further modeling Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics

Comprehensive Geographic Information Systems

Comprehensive Geographic Information Systems PDF Author:
Publisher: Elsevier
ISBN: 0128047933
Category : Science
Languages : en
Pages : 1488

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Book Description
Geographical Information Systems, Three Volume Set is a computer system used to capture, store, analyze and display information related to positions on the Earth’s surface. It has the ability to show multiple types of information on multiple geographical locations in a single map, enabling users to assess patterns and relationships between different information points, a crucial component for multiple aspects of modern life and industry. This 3-volumes reference provides an up-to date account of this growing discipline through in-depth reviews authored by leading experts in the field. VOLUME EDITORS Thomas J. Cova The University of Utah, Salt Lake City, UT, United States Ming-Hsiang Tsou San Diego State University, San Diego, CA, United States Georg Bareth University of Cologne, Cologne, Germany Chunqiao Song University of California, Los Angeles, CA, United States Yan Song University of North Carolina at Chapel Hill, Chapel Hill, NC, United States Kai Cao National University of Singapore, Singapore Elisabete A. Silva University of Cambridge, Cambridge, United Kingdom Covers a rapidly expanding discipline, providing readers with a detailed overview of all aspects of geographic information systems, principles and applications Emphasizes the practical, socioeconomic applications of GIS Provides readers with a reliable, one-stop comprehensive guide, saving them time in searching for the information they need from different sources

Encyclopedia of GIS

Encyclopedia of GIS PDF Author: Shashi Shekhar
Publisher: Springer Science & Business Media
ISBN: 038730858X
Category : Computers
Languages : en
Pages : 1392

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Book Description
The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features.

Geographically Weighted Regression

Geographically Weighted Regression PDF Author: A. Stewart Fotheringham
Publisher: John Wiley & Sons
ISBN: 0470855258
Category : Science
Languages : en
Pages : 282

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Book Description
Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).