Da: Majestic Books, Hounslow, Regno Unito
EUR 134,59
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. 286.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 286.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 152,36
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. 286.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 155,71
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
EUR 122,70
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Spatial Regression Analysis Using Eigenvector Spatial Filtering | Daniel Griffith (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2019 | Academic Press | EAN 9780128150436 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 181,97
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 118,91
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Da: Revaluation Books, Exeter, Regno Unito
EUR 133,64
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 432 pages. 8.90x5.90x0.70 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Elsevier Science & Technology, Academic Press, 2019
ISBN 10: 0128150432 ISBN 13: 9780128150436
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 132,00
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre. Englisch.
Lingua: Inglese
Editore: Elsevier Science & Technology|Academic Press, 2019
ISBN 10: 0128150432 ISBN 13: 9780128150436
Da: moluna, Greven, Germania
EUR 130,54
Quantità: Più di 20 disponibili
Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical meth.
Lingua: Inglese
Editore: Elsevier Science & Technology, Academic Press, 2019
ISBN 10: 0128150432 ISBN 13: 9780128150436
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 145,16
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre.