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Emily St. John Mandel: IMG Powell’s Q&A: Emily St. John Mandel



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    Station Eleven

    Emily St. John Mandel 9780385353304

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Spatial and Spatio-Temporal Data Analysis (Focus)

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Synopses & Reviews

Publisher Comments:

This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.
Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.
The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach.
This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics.

Synopsis:

This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.
Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.
The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach.
This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics.

Synopsis:

This book offers a clear, highly readable introduction to spatial analyses about the disaggregated, or micro, spatial data. It presents the application of spatial analysis methods, while focusing on the recent developments in the field. Special emphasis is given to spatial data compilation and the structuring of the connections between the observations. Additional coverage includes descriptive analysis methods of spatial data and autoregressive spatial models. An top-notch reference for readers without advanced statistical theoretical basics, who are interested in working with spatialized data.

Table of Contents

Chapter 1 – Introduction to spatial data

Chapter 2 – Structuring spatial relationships: role of the weighing matrix

Chapter 3 – Exploratory analysis methods of datato detect patterns of spatial dependence between observations. (Global and local) spatial autocorrelation is formally tackled and described and the statistics to detect these patterns are also presented. The “problem” related to the presence of spatial autocorrelation can lead to complications in the analyzes of conventional multiple linear regressions.

Chapter 4 – Modeling of spatial effects

Chapter 5 – Spatio-temporal considerations

Chapter 6 – Conclusion

Product Details

ISBN:
9781848214682
Publisher:
Wiley-ISTE
Subject:
Numerical Methods & Algorithms
Author:
Dube, Jean-Claude
Author:
Dub?, Jean
Author:
Dub
Author:
Legros, Di?go
Author:
&
Author:
Jean Dub
Author:
Jean
Author:
eacute
Subject:
Software Engineering-Algorithms
Subject:
Spatial and Spatio-temporal Data Analysis, Spatial Relationships, Spatial Dependence Between Observations, Spatial Autocorrelation, Spatial Data, Autoregressive Spatial Models
Copyright:
Edition Description:
WOL online Book (not BRO)
Series:
ISTE
Publication Date:
20130628
Binding:
Electronic book text in proprietary or open standard format
Language:
English
Pages:
208

Related Subjects

Computers and Internet » Computers Reference » General
Computers and Internet » Software Engineering » Algorithms
Transportation » Automotive » General

Spatial and Spatio-Temporal Data Analysis (Focus)
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Product details 208 pages Wiley-Iste - English 9781848214682 Reviews:
"Synopsis" by , This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.
Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.
The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach.
This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics.
"Synopsis" by , This book offers a clear, highly readable introduction to spatial analyses about the disaggregated, or micro, spatial data. It presents the application of spatial analysis methods, while focusing on the recent developments in the field. Special emphasis is given to spatial data compilation and the structuring of the connections between the observations. Additional coverage includes descriptive analysis methods of spatial data and autoregressive spatial models. An top-notch reference for readers without advanced statistical theoretical basics, who are interested in working with spatialized data.
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