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Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)
Daniel P. McMillen
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Description for Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)
Paperback. Shows how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. This book is to make quantile regression procedures more accessible for researchers working with spatial data sets. Series: Springerbriefs in Regional Science. Num Pages: 80 pages, 47 black & white illustrations, 14 black & white tables, biography. BIC Classification: KCP. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 4. Weight in Grams: 132.
Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. Despite its advantages, quantile regression is still not commonly used in the analysis of spatial data. The objective of this book is to make quantile regression procedures more accessible for researchers working with spatial data sets. The emphasis is on interpretation of quantile regression results. A series of examples using both simulated ... Read more
Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. Despite its advantages, quantile regression is still not commonly used in the analysis of spatial data. The objective of this book is to make quantile regression procedures more accessible for researchers working with spatial data sets. The emphasis is on interpretation of quantile regression results. A series of examples using both simulated ... Read more
Product Details
Publisher
Springer
Format
Paperback
Publication date
2012
Series
Springerbriefs in Regional Science
Condition
New
Weight
138g
Number of Pages
66
Place of Publication
Berlin, Germany
ISBN
9783642318146
SKU
V9783642318146
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Daniel P. McMillen
Daniel McMillen is a Professor of Economics at the University of Illinois, with a joint appointment in the Institute of Government and Public Affairs. He serves as co-editor of Regional Science and Economics.
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