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Morphisms for quantitative spatial a...

Griffith, Daniel A.

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Morphisms for quantitative spatial analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Morphisms for quantitative spatial analysis/ by Daniel A. Griffith, Jean H. P. Paelinck.
作者:	Griffith, Daniel A.
其他作者:	Paelinck, Jean H. P.
出版者:	Cham :Springer International Publishing : : 2018.,
面頁冊數:	xiii, 258 p. :ill., digital ;24 cm.
內容註:	Preamble -- Introduction to Part 1: Spatial statistics -- Spatial autocorrelation and the p-Median problem -- Space-time autocorrelation -- The relative importance of spatial and temporal autocorrelation -- The spatial weights matrix and ESF -- Clustering: Spatial autocorrelation and location quotients -- Spatial autocorrelation parameter estimation for massively large georeferenced datasets -- Space-time data and semi-saturated fixed effects -- Spatial autocorrelation and spatial interaction gravity models -- General conclusions about spatial statistics -- Introduction to Part 2: Spatial econometrics -- Tinbergen-Bos systems: Combining combinatorial analysis with metric topology -- Time, space, or econotimespace?- Hybrid dynamical systems and control -- The W matrix revisited -- Clustering, some non-standard approaches -- Linear expenditure systems and related estimation problems -- Structural indicators galore -- Traveling with the salesman -- Complexer and complexer, said Alice -- General conclusions about spatial econometrics -- Epilogue -- References -- Subject index -- Author's index.
Contained By:	Springer eBooks
標題:	Spatial analysis (Statistics) -
電子資源:	http://dx.doi.org/10.1007/978-3-319-72553-6
ISBN:	9783319725536

Morphisms for quantitative spatial analysis
Griffith, Daniel A.

Morphisms for quantitative spatial analysis[electronic resource] /by Daniel A. Griffith, Jean H. P. Paelinck. - Cham :Springer International Publishing :2018. - xiii, 258 p. :ill., digital ;24 cm. - Advanced studies in theoretical and applied econometrics,v.511570-5811 ;. - Advanced studies in theoretical and applied econometrics ;v.51..

Preamble -- Introduction to Part 1: Spatial statistics -- Spatial autocorrelation and the p-Median problem -- Space-time autocorrelation -- The relative importance of spatial and temporal autocorrelation -- The spatial weights matrix and ESF -- Clustering: Spatial autocorrelation and location quotients -- Spatial autocorrelation parameter estimation for massively large georeferenced datasets -- Space-time data and semi-saturated fixed effects -- Spatial autocorrelation and spatial interaction gravity models -- General conclusions about spatial statistics -- Introduction to Part 2: Spatial econometrics -- Tinbergen-Bos systems: Combining combinatorial analysis with metric topology -- Time, space, or econotimespace?- Hybrid dynamical systems and control -- The W matrix revisited -- Clustering, some non-standard approaches -- Linear expenditure systems and related estimation problems -- Structural indicators galore -- Traveling with the salesman -- Complexer and complexer, said Alice -- General conclusions about spatial econometrics -- Epilogue -- References -- Subject index -- Author's index.

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.

ISBN: 9783319725536

Standard No.: 10.1007/978-3-319-72553-6doiSubjects--Topical Terms:

520421
Spatial analysis (Statistics)

LC Class. No.: QA278.2 / .G754 2018

Dewey Class. No.: 519.5

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245 1 0 $a Morphisms for quantitative spatial analysis $h [electronic resource] / $c by Daniel A. Griffith, Jean H. P. Paelinck.
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505 0 $a Preamble -- Introduction to Part 1: Spatial statistics -- Spatial autocorrelation and the p-Median problem -- Space-time autocorrelation -- The relative importance of spatial and temporal autocorrelation -- The spatial weights matrix and ESF -- Clustering: Spatial autocorrelation and location quotients -- Spatial autocorrelation parameter estimation for massively large georeferenced datasets -- Space-time data and semi-saturated fixed effects -- Spatial autocorrelation and spatial interaction gravity models -- General conclusions about spatial statistics -- Introduction to Part 2: Spatial econometrics -- Tinbergen-Bos systems: Combining combinatorial analysis with metric topology -- Time, space, or econotimespace?- Hybrid dynamical systems and control -- The W matrix revisited -- Clustering, some non-standard approaches -- Linear expenditure systems and related estimation problems -- Structural indicators galore -- Traveling with the salesman -- Complexer and complexer, said Alice -- General conclusions about spatial econometrics -- Epilogue -- References -- Subject index -- Author's index.
520 $a 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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650 0 $a Space in economics $x Statistical methods. $3 3308376
650 0 $a Econometrics. $3 542934
650 1 4 $a Economics. $3 517137
650 2 4 $a Geographical Information Systems/Cartography. $3 890881
650 2 4 $a Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. $3 894294
650 2 4 $a Regional/Spatial Science. $3 1001622
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 1005896
650 2 4 $a Humanities and Social Sciences, multidisciplinary. $3 3227905
700 1 $a Paelinck, Jean H. P. $3 3308374
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