Quantile Regression for Spatial Data by Daniel P. McMillen (English) Paperback B

Description: Quantile Regression for Spatial Data by Daniel P. McMillen Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. A series of examples using both simulated and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description 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 and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. Both parametric and nonparametric versions of spatial models are considered in detail. Notes Emphasis on graphical interpretation of quantile regression resultsPresents estimators designed specifically for the analysis of spatial dataIncludes both parametric and nonparametric approachesIncludes both parametric and nonparametric Back Cover 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 and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. Both parametric and nonparametric versions of spatial models are considered in detail. Author Biography 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. Table of Contents 1 Quantile Regression: An Overview. 2 Linear and Nonparametric Quantile Regression.- 3 A Quantile Regression Analysis of Assessment Regressivity.-4 Quantile Version of the Spatial AR Model.- 5 . Conditionally Parametric Quantile Regression.- 6 Guide to Further Reading.- References. Feature Emphasis on graphical interpretation of quantile regression results Presents estimators designed specifically for the analysis of spatial data Includes both parametric and nonparametric approaches Includes both parametric and nonparametric Details ISBN3642318142 Author Daniel P. McMillen Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Year 2012 ISBN-10 3642318142 ISBN-13 9783642318146 Format Paperback Publication Date 2012-08-01 Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K Place of Publication Berlin Country of Publication Germany DEWEY 338.7 Short Title QUANTILE REGRESSION FOR SPATIA Language English Media Book Pages 66 Edition 2013th DOI 10.1007/978-3-642-31815-3 Edition Description 2013 ed. Audience Professional & Vocational Series SpringerBriefs in Regional Science Illustrations 47 Illustrations, black and white; IX, 66 p. 47 illus. We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96268555;

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