Quantile Regression for Spatial Data (SpringerBriefs in Regional Science) - Softcover

Buch 2 von 10: SpringerBriefs in Regional Science

McMillen, Daniel P.

 
9783642318146: Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)
Softcover
ISBN 10: 3642318142 ISBN 13: 9783642318146
Verlag: Springer, 2012

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

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.

Von der hinteren Coverseite

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.

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Verlag
Springer
Erscheinungsdatum
2012
Sprache
Englisch
ISBN 10 
3642318142
ISBN 13 
9783642318146
Einband
Taschenbuch
Anzahl der Seiten
76
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