Spatial Error Analysis
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Spatial Error Analysis
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Author : David Y. Hsu
language : en
Publisher: Wiley-IEEE Press
Release Date : 1998-09-04
Spatial Error Analysis written by David Y. Hsu and has been published by Wiley-IEEE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-09-04 with Technology & Engineering categories.
"SPATIAL ERROR ANALYSIS is an all-in-one sourcebook on error measurements in one-, two-, and three-dimensional spaces. This book features exhaustive, systematic coverage of error measurement relationships, techniques, and solutions used to solve general, correlated cases. It is packed with 62 figures and 24 tables. MATLAB-based M-files* for practical applications created especially for this volume are available on the Web at ftp://ftp.mathworks.com/pub/books/hsu. Solutions to two- and three-dimensional problems are presented without relying on equal standard deviations from each channel. They also make no assumption that the random variables of interest are independent or uncorrelated. * MATLAB (developed by MathWorks, Inc.) must be purchased separately." Sponsored by: IEEE Aerospace and Electronic Systems Society.
Spatial Data Analysis
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Author : Manfred M. Fischer
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-05
Spatial Data Analysis written by Manfred M. Fischer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-05 with Business & Economics categories.
The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focuses on detecting patterns, and on exploring and modelling relationships between them in order to understand the processes responsible for their emergence. In this way, the role of space is emphasised , and our understanding of the working and representation of space, spatial patterns, and processes is enhanced. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered.
Spatial Regression Models
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Author : Michael Don Ward
language : en
Publisher: SAGE
Release Date : 2008-02-29
Spatial Regression Models written by Michael Don Ward and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-29 with Mathematics categories.
Assuming no prior knowledge this book is geared toward social science readers, unlike other volumes on this topic. The text illustrates concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside relevant data and code, which is also available on a Web site maintained by the authors.
Adjustment Computations
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Author : Charles D. Ghilani
language : en
Publisher:
Release Date : 2018
Adjustment Computations written by Charles D. Ghilani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Spatial analysis (Statistics) categories.
Spatial Analysis For The Social Sciences
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Author : David Darmofal
language : en
Publisher: Cambridge University Press
Release Date : 2015-11-12
Spatial Analysis For The Social Sciences written by David Darmofal and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-12 with Mathematics categories.
This book shows how to model the spatial interactions between actors that are at the heart of the social sciences.
Principles Of Modeling Uncertainties In Spatial Data And Spatial Analyses
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Author : Wenzhong Shi
language : en
Publisher: CRC Press
Release Date : 2009-09-30
Principles Of Modeling Uncertainties In Spatial Data And Spatial Analyses written by Wenzhong Shi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-30 with Mathematics categories.
When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of t
Spatial Data Analysis In Ecology And Agriculture Using R
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Author : Richard E. Plant
language : en
Publisher: CRC Press
Release Date : 2012-03-07
Spatial Data Analysis In Ecology And Agriculture Using R written by Richard E. Plant and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-07 with Mathematics categories.
Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author’s spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
Error Propagation In Quantitative Spatial Modelling
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Author : Gerard B. M. Heuvelink
language : en
Publisher:
Release Date : 1993
Error Propagation In Quantitative Spatial Modelling written by Gerard B. M. Heuvelink and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Cartography categories.
Statistical Methods For Spatial Data Analysis
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Author : Oliver Schabenberger
language : en
Publisher: CRC Press
Release Date : 2017-01-27
Statistical Methods For Spatial Data Analysis written by Oliver Schabenberger and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Mathematics categories.
Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.
The Econometric Analysis Of Non Stationary Spatial Panel Data
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Author : Michael Beenstock
language : en
Publisher: Springer
Release Date : 2019-03-27
The Econometric Analysis Of Non Stationary Spatial Panel Data written by Michael Beenstock and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-27 with Business & Economics categories.
This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.