Daniel A. Griffith's Books

Spatial Autocorrelation and Spatial Filtering

Gaining Understanding Through Theory and Scientific Visualization

By: Daniel A. Griffith

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Spatial Autocorrelation and Spatial Filtering

Gaining Understanding Through Theory and Scientific Visualization

By: Daniel A. Griffith

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.

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Page Count

261

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3540248064

ISBN 13

9783540248064

Morphisms for Quantitative Spatial Analysis

By: Daniel A. Griffith,Jean H. P. Paelinck

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Morphisms for Quantitative Spatial Analysis

By: Daniel A. Griffith,Jean H. P. Paelinck

This book treats the notion of morphisms in spatial analysis, paralleling these concepts in spatial statistics (Part I) and spatial econometrics (Part II). The principal concept is morphism (e.g., isomorphisms, homomorphisms, and allomorphisms), which is defined as a structure preserving the functional linkage between mathematical properties or operations in spatial statistics and spatial econometrics, among other disciplines. The purpose of this book is to present selected conceptions in both domains that are structurally the same, even though their labelling and the notation for their elements may differ. As the approaches presented here are applied to empirical materials in geography and economics, the book will also be of interest to scholars of regional science, quantitative geography and the geospatial sciences. It is a follow-up to the book “Non-standard Spatial Statistics and Spatial Econometrics” by the same authors, which was published by Springer in 2011.

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Page Count

272

Publisher

Springer

Published Date

ISBN 10

331972553X

ISBN 13

9783319725536

Non-standard Spatial Statistics and Spatial Econometrics

By: Daniel A. Griffith,Jean H. Paul Paelinck

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Non-standard Spatial Statistics and Spatial Econometrics

By: Daniel A. Griffith,Jean H. Paul Paelinck

Despite spatial statistics and spatial econometrics both being recent sprouts of the general tree "spatial analysis with measurement"—some may remember the debate after WWII about "theory without measurement" versus "measurement without theory"—several general themes have emerged in the pertaining literature. But exploring selected other fields of possible interest is tantalizing, and this is what the authors intend to report here, hoping that they will suscitate interest in the methodologies exposed and possible further applications of these methodologies. The authors hope that reactions about their publication will ensue, and they would be grateful to reader(s) motivated by some of the research efforts exposed hereafter letting them know about these experiences.

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Page Count

277

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3642160433

ISBN 13

9783642160431

Advanced Spatial Statistics

Special Topics in the Exploration of Quantitative Spatial Data Series

By: Daniel A. Griffith

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Advanced Spatial Statistics

Special Topics in the Exploration of Quantitative Spatial Data Series

By: Daniel A. Griffith

In recent years there has been a growing interest in and concern for the development of a sound spatial statistical body of theory. This work has been undertaken by geographers, statisticians, regional scientists, econometricians, and others (e. g. , sociologists). It has led to the publication of a number of books, including Cliff and Ord's Spatial Processes (1981), Bartlett's The Statistical Analysis of Spatial Pattern (1975), Ripley's Spatial Statistics (1981), Paelinck and Klaassen's Spatial Economet~ics (1979), Ahuja and Schachter's Pattern Models (1983), and Upton and Fingleton's Spatial Data Analysis by Example (1985). The first of these books presents a useful introduction to the topic of spatial autocorrelation, focusing on autocorrelation indices and their sampling distributions. The second of these books is quite brief, but nevertheless furnishes an eloquent introduction to the rela tionship between spatial autoregressive and two-dimensional spectral models. Ripley's book virtually ignores autoregressive and trend surface modelling, and focuses almost solely on point pattern analysis. Paelinck and Klaassen's book closely follows an econometric textbook format, and as a result overlooks much of the important material necessary for successful spatial data analy sis. It almost exclusively addresses distance and gravity models, with some treatment of autoregressive modelling. Pattern Models supplements Cliff and Ord's book, which in combination provide a good introduction to spatial data analysis. Its basic limitation is a preoccupation with the geometry of planar patterns, and hence is very narrow in scope.

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Page Count

286

Publisher

Springer Science & Business Media

Published Date

ISBN 10

9400927584

ISBN 13

9789400927582

Spatial Statistics and Geostatistics

Theory and Applications for Geographic Information Science and Technology

By: Yongwan Chun,Daniel A Griffith

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Spatial Statistics and Geostatistics

Theory and Applications for Geographic Information Science and Technology

By: Yongwan Chun,Daniel A Griffith

Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.

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Page Count

201

Publisher

SAGE

Published Date

ISBN 10

1446272117

ISBN 13

9781446272114

Spatial Regression Analysis Using Eigenvector Spatial Filtering

By: Daniel Griffith,Yongwan Chun,Bin Li

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Spatial Regression Analysis Using Eigenvector Spatial Filtering

By: Daniel Griffith,Yongwan Chun,Bin Li

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

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Page Count

288

Publisher

Academic Press

Published Date

ISBN 10

0128156929

ISBN 13

9780128156926

Andy and Don

The Making of a Friendship and a Classic American TV Show

By: Daniel de Visé

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Andy and Don

The Making of a Friendship and a Classic American TV Show

By: Daniel de Visé

When Andy Griffith went to Hollywood in 1960 to film a TV pilot about a small-town sheriff, his friend Don Knotts called to ask if his sheriff could use a deputy. Together, Sheriff Andy Taylor and Deputy Barney Fife elevated The Andy Griffith Show from a folksy sitcom into a timeless study of human friendship. The program was fiction, but the friendship was powerful and real."--Jacket.

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Page Count

320

Publisher

Simon and Schuster

Published Date

ISBN 10

1476747741

ISBN 13

9781476747743

The Econometric Analysis of Non-Stationary Spatial Panel Data

By: Michael Beenstock,Daniel Felsenstein

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The Econometric Analysis of Non-Stationary Spatial Panel Data

By: Michael Beenstock,Daniel Felsenstein

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.

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Page Count

280

Publisher

Springer

Published Date

ISBN 10

3030036146

ISBN 13

9783030036140

Advanced Introduction to Spatial Statistics

By: Griffith, Daniel A.,Li, Bin

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Advanced Introduction to Spatial Statistics

By: Griffith, Daniel A.,Li, Bin

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.

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Page Count

125

Publisher

Edward Elgar Publishing

Published Date

ISBN 10

1800372825

ISBN 13

9781800372825

Petroleum Production Systems

By: A. Daniel Hill,Michael J. Economides,Christine Ehlig-Economides,Ding Zhu

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Petroleum Production Systems

By: A. Daniel Hill,Michael J. Economides,Christine Ehlig-Economides,Ding Zhu

The Definitive Guide to Petroleum Production Systems–Now Fully Updated With the Industry’s Most Valuable New Techniques Petroleum Production Systems, Second Edition, is the comprehensive source for clear and fundamental methods for about modern petroleum production engineering practice. Written by four leading experts, it thoroughly introduces modern principles of petroleum production systems design and operation, fully considering the combined behavior of reservoirs, surface equipment, pipeline systems, and storage facilities. Long considered the definitive text for production engineers, this edition adds extensive new coverage of hydraulic fracturing, with emphasis on well productivity optimization. It presents new chapters on horizontal wells and well performance evaluation, including production data analysis and sand management. This edition features A structured approach spanning classical production engineering, well testing, production logging, artificial lift, and matrix and hydraulic fracture stimulation Revisions throughout to reflect recent innovations and extensive feedback from both students and colleagues Detailed coverage of modern best practices and their rationales Unconventional oil and gas well design Many new examples and problems Detailed data sets for three characteristic reservoir types: an undersaturated oil reservoir, a saturated oil reservoir, and a gas reservoir

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Page Count

752

Publisher

Prentice Hall

Published Date

ISBN 10

0137033257

ISBN 13

9780137033256

Book's by Daniel A. Griffith

Spatial Autocorrelation and Spatial Filtering

Spatial Autocorrelation and Spatial Filtering

Morphisms for Quantitative Spatial Analysis

Morphisms for Quantitative Spatial Analysis

Non-standard Spatial Statistics and Spatial Econometrics

Non-standard Spatial Statistics and Spatial Econometrics

Advanced Spatial Statistics

Advanced Spatial Statistics

Spatial Statistics and Geostatistics

Spatial Statistics and Geostatistics

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Andy and Don

Andy and Don

The Econometric Analysis of Non-Stationary Spatial Panel Data

The Econometric Analysis of Non-Stationary Spatial Panel Data

Advanced Introduction to Spatial Statistics

Advanced Introduction to Spatial Statistics

Petroleum Production Systems

Petroleum Production Systems

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