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Quantile Regression Spatial Data by Mcmillen Daniel (15 results)
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Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)
Book 2 of 10: SpringerBriefs in Regional SciencePublished by Springer (edition 2013), 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
Paperback. Condition: Good. 2013. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional SciencePublished by Springer Berlin / Heidelberg, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
Seller: Better World Books Ltd, Dunfermline, United Kingdom
Seller rating 5 out of 5 stars
Condition: Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.
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Paperback or Softback. Condition: New. Quantile Regression for Spatial Data. Book.
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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
Condition: New. In.
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PF. Condition: New.
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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 SciencePublished by Springer Berlin Heidelberg, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
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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Quantile Regression for Spatial Data
Book 2 of 10: SpringerBriefs in Regional SciencePublished by Springer-Verlag GmbH, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
Taschenbuch. Condition: Neu. Quantile Regression for Spatial Data | Daniel P. Mcmillen | Taschenbuch | ix | Englisch | 2012 | Springer-Verlag GmbH | 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 SciencePublished by Springer Berlin Heidelberg Aug 2012, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
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 SciencePublished by Springer Berlin Heidelberg, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
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 SciencePublished by Springer Berlin Heidelberg, J.B. Metzler Aug 2012, 2012
ISBN 10: 3642318142 ISBN 13: 9783642318146
Language: English
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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 76 pp. Englisch.
