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Quantile Regression Spatial Data by Mcmillen Daniel (17 results)
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Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)
Book 2 of 10: SpringerBriefs in Regional ScienceLanguage: English
Published by Springer (edition 2013), 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Paperback. Condition: Very Good. 2013. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Paperback or Softback. Condition: New. Quantile Regression for Spatial Data. Book.
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Condition: As New. Unread book in perfect condition.
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Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)
Book 2 of 10: SpringerBriefs in Regional ScienceSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 59.14
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional ScienceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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PF. Condition: New.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional ScienceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New. pp. 78.
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Paperback. Condition: Brand New. 2013 edition. 75 pages. 9.20x6.40x1.00 inches. In Stock.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional ScienceLanguage: English
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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Taschenbuch. Condition: Neu. Quantile Regression for Spatial Data | Daniel P. Mcmillen | Taschenbuch | SpringerBriefs in Regional Science | ix | Englisch | 2012 | Springer | EAN 9783642318146 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional ScienceLanguage: English
Published by Springer Berlin Heidelberg Aug 2012, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 76 pp. Englisch.
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Condition: New. Print on Demand pp. 78 47 Illus.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional ScienceLanguage: English
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Emphasis on graphical interpretation of quantile regression resultsPresents estimators designed specifically for the analysis of spatial data Includes both parametric and nonparametric approaches Includes both parametric and nonparam.
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Condition: New. PRINT ON DEMAND pp. 78.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional ScienceLanguage: English
Published by Springer, Springer Aug 2012, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 76 pp. Englisch.
