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Item Details
Title:
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QUANTILE REGRESSION FOR SPATIAL DATA
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By: |
Daniel P. McMillen |
Format: |
Paperback |
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List price:
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£49.99 |
We currently do not stock this item, please contact the publisher directly for
further information.
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ISBN 10: |
3642318142 |
ISBN 13: |
9783642318146 |
Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
Pub. date: |
1 August, 2012 |
Edition: |
2013 ed. |
Series: |
SpringerBriefs in Regional Science |
Pages: |
66 |
Description: |
Shows 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. This book is to make quantile regression procedures more accessible for researchers working with spatial data sets. |
Synopsis: |
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. |
Illustrations: |
14 Tables, black and white; 47 Illustrations, black and white; IX, 66 p. 47 |
Publication: |
Germany |
Imprint: |
Springer-Verlag Berlin and Heidelberg GmbH & Co. K |
Returns: |
Returnable |
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