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Book Cover
E-book
Author McMillen, Daniel P.

Title Quantile regression for spatial data / Daniel P. McMillen
Published Berlin ; New York : Springer, ©2013

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Description 1 online resource (ix, 66 pages) : illustrations (some color)
Series SpringerBriefs in regional science, 2192-0427
SpringerBriefs in regional science.
Contents Quantile Regression: An Overview -- Linear and Nonparametric Quantile Regression -- A Quantile Regression Analysis of Assessment Regressivity -- Quantile Version of the Spatial AR Model -- Conditionally Parametric Quantile Regression -- Guide to Further Reading
Summary 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
Analysis Economics
Regional economics
Economics/Management Science
Regional/Spatial Science
Bibliography Includes bibliographical references
Notes Original print version
Subject Regression analysis.
Spatial analysis (Statistics)
Regression Analysis
spatial analysis.
MATHEMATICS -- Probability & Statistics -- Regression Analysis.
Science économique.
Affaires.
Regression analysis
Spatial analysis (Statistics)
Raumdaten
Regressionsanalyse
Form Electronic book
ISBN 9783642318153
3642318150
3642318142
9783642318146