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Spatial socio-econometric modeling (...

Gonzalez Canche, Manuel S.

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Spatial socio-econometric modeling (SSEM) = a low-code toolkit for spatial data science and interactive visualizations using R /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Spatial socio-econometric modeling (SSEM)/ by Manuel S. Gonzalez Canche.
Reminder of title:	a low-code toolkit for spatial data science and interactive visualizations using R /
Author:	Gonzalez Canche, Manuel S.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xli, 503 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I Conceptual and Theoretical Underpinnings -- Chapter 1. SPlaces -- Chapter 2. Operationalizing Splaces -- Chapter 3. Data Formats, Coordinate Reference Systems, and Differential Privacy Frameworks -- Part II Data Science SSEM Identification Tools: Distances, Networks, and Neighbors -- Chapter 4. Access and Management of Spatial or Geocoded Data -- Chapter 5. Distances -- Chapter 6. Geographical Networks as Identification Tools -- Part III SSEM Hypothesis Testing of Cross-sectional and Spatio-temporal Data and Interactive Visualizations -- Chapter 7. SODA: Spatial Outcome Dependence or Autocorrelation -- Chapter 8. SSEM Regression Based analyses -- Chapter 9. Visualization, Mining, and Density Analyses of Spatial and Spatio-temporal Data -- Chapter 10. Final Words -- Glossary -- Index.
Contained By:	Springer Nature eBook
Subject:	Social sciences - Statistical methods. -
Online resource:	https://doi.org/10.1007/978-3-031-24857-3
ISBN:	9783031248573

Spatial socio-econometric modeling (SSEM) = a low-code toolkit for spatial data science and interactive visualizations using R /
Gonzalez Canche, Manuel S.

Spatial socio-econometric modeling (SSEM)a low-code toolkit for spatial data science and interactive visualizations using R /[electronic resource] :by Manuel S. Gonzalez Canche. - Cham :Springer International Publishing :2023. - xli, 503 p. :ill., digital ;24 cm. - Springer texts in social sciences,2730-6143. - Springer texts in social sciences..

Part I Conceptual and Theoretical Underpinnings -- Chapter 1. SPlaces -- Chapter 2. Operationalizing Splaces -- Chapter 3. Data Formats, Coordinate Reference Systems, and Differential Privacy Frameworks -- Part II Data Science SSEM Identification Tools: Distances, Networks, and Neighbors -- Chapter 4. Access and Management of Spatial or Geocoded Data -- Chapter 5. Distances -- Chapter 6. Geographical Networks as Identification Tools -- Part III SSEM Hypothesis Testing of Cross-sectional and Spatio-temporal Data and Interactive Visualizations -- Chapter 7. SODA: Spatial Outcome Dependence or Autocorrelation -- Chapter 8. SSEM Regression Based analyses -- Chapter 9. Visualization, Mining, and Density Analyses of Spatial and Spatio-temporal Data -- Chapter 10. Final Words -- Glossary -- Index.

ISBN: 9783031248573

Standard No.: 10.1007/978-3-031-24857-3doiSubjects--Topical Terms:

529420
Social sciences
--Statistical methods.

LC Class. No.: HA29 / .G66 2023

Dewey Class. No.: 300.15195

Spatial socio-econometric modeling (SSEM) = a low-code toolkit for spatial data science and interactive visualizations using R /
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505 0 $a Part I Conceptual and Theoretical Underpinnings -- Chapter 1. SPlaces -- Chapter 2. Operationalizing Splaces -- Chapter 3. Data Formats, Coordinate Reference Systems, and Differential Privacy Frameworks -- Part II Data Science SSEM Identification Tools: Distances, Networks, and Neighbors -- Chapter 4. Access and Management of Spatial or Geocoded Data -- Chapter 5. Distances -- Chapter 6. Geographical Networks as Identification Tools -- Part III SSEM Hypothesis Testing of Cross-sectional and Spatio-temporal Data and Interactive Visualizations -- Chapter 7. SODA: Spatial Outcome Dependence or Autocorrelation -- Chapter 8. SSEM Regression Based analyses -- Chapter 9. Visualization, Mining, and Density Analyses of Spatial and Spatio-temporal Data -- Chapter 10. Final Words -- Glossary -- Index.
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