Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

Austrian Post 5.49 € DPD courier 3.99 € DPD point 2.99 €

Contact

How to shop

Help

My account

▸ Empty :-(

Proximity Catch Digraphs

Name: Proximity Catch Digraphs
Brand: VDM Verlag Dr. Müller
SKU: 06827174
Price: 83.09 EUR
Availability: InStock
Author: Elvan Ceyhan
ISBN: 9783639190632

Auxiliary Tools, Properties, and Applications

Elvan Ceyhan

Language

English

Book Paperback

Libristo code: 06827174

Publishers VDM Verlag Dr. Müller, November 2008

This book introduces proximity catch digraphs (PCDs) based on multiple types of data points in a mea... Full description

Libristo code: 06827174

203 b

83.09 € VAT included

Print on demand Shipping in 17-27 days

Delivery to Austria

30-day return policy

Customers also purchased

Gerichtsöffentlichkeit durch Fernsehberichterstattung Christian Burock

Paperback

89.90 €

Diagnostico de La Escuela Tecnica En Mendoza (Argentina) Anahí Catalina Fracaro

Paperback

45.79 €

Young ELI Readers 3/A1.1: Five Children and It + Downloadable Multimedia Edith Nesbit

Paperback

13.49 €

EN PLEIN AIR - IM FREIEN - OUT OF DOORS - VOLUME 1 - PIECES 1 A 3 BELA BARTOK Book

Paperback

44.39 €

Dalajlamova kočka - Probuď v sobě kotě David Michie

Hardback

11.19 €

Capria 1 - Despierta tu magia MARTINA D'ANTIOCHIA

Hardback

18.99 €

This book introduces proximity catch digraphs (PCDs) based on multiple types of data points in a measurable space. The PCDs are constructed using the relative positions of members of points from a class of interest with respect to the Delaunay tessellation of points from another class. Among the advantages of PCDs is mathematical tractability of the distribution of the domination number, moments of relative density, and geometry invariance for uniform data. Thus PCDs are applicable on statistical hypothesis testing and pattern classification. The domination number and relative density are both used to test a type of complete spatial randomness against spatial point patterns of segregation and association. The power of the tests is assessed by asymptotic efficiency methods such as Pitman asymptotic efficiency, Hodges-Lehmann asymptotic efficiency, and asymptotic power function analysis. Finite sample power is analyzed by extensive Monte Carlo simulations. The methods are illustrated in the two dimensional case, but are applicable to higher dimensions as well as to other types of proximity maps.