Spatial regression models by Michael d. Ward
Publication details: Sage New Delhi 2019Edition: 2nd EdDescription: xv, 112 pages; illustrations: 21 cmISBN:- 9781544328836
- 519.5
Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
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Book | Indian Institute of Management Visakhapatnam - Andhra University | 519.5 (Browse shelf(Opens below)) | Available | 001453 WAR | |||
Book | Indian Institute of Management Visakhapatnam General Stacks | Non-fiction | 519.5 WAR (Browse shelf(Opens below)) | Checked out | 04/23/2023 | 001253 |
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519.3 CHA A Course on Cooperative Game Theory | 519.5 CHE Straightforward Statistics | 519.5 KNO Log-linear models: Quantitative Applications in the Social Sciences | 519.5 WAR Spatial regression models | 519.50243 SUL Multiple indicators: an introduction | 519.502465 Statistics for Business: Decision Making and Analysis | 519.502465 STI Statistics for Business: Decision Making and Analysis |
Chapter 1: Why Space in the Social Sciences? Chapter 2: Maps as Displays of Information Chapter 3: Interdependency Among Observations Chapter 4: Spatially Lagged Dependent Variables Chapter 5: Spatial Error Model Chapter 6: Extensions
patial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The text covers different modeling-related topics for continuous dependent variables, including mapping data on spatial units, creating data from maps, analyzing exploratory spatial data, working with regression models that have spatially dependent regressors, and estimating regression models with spatially correlated error structures.
Using social science examples based on real data, the authors illustrate the concepts discussed, and show how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the R package for statistical computing. Users can download both the data and computer code to work through all the examples found in the text. New to the Second Edition is a chapter on mapping as data exploration and its role in the research process, updates to all chapters based on substantive and methodological work, as well as software updates, and information on estimation of time-series, cross-sectional spatial models.
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