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Herausgeber: 
  • David G.T. Denison
  • Lawson Andrew B.
  • Spatial Cluster Modelling 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Januar 2020  
    Genre:  Schulbücher 
     
    advanced spatial cluster techniques / Bayesian spatial analysis / Biology, life sciences / disease mapping methods / ecological data clustering / MATHEMATICS / Probability & Statistics / General / neuroimaging statistics / point process inference
    ISBN:  9780367454913 
    EAN-Code: 
    9780367454913 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Gewicht:  560 gr 
    Seiten:  308 
    Illustration:  schwarz-weiss Illustrationen, farbige Illustrationen, Raster,schwarz-weiss, Tabellen, schwarz-weiss 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling. Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.

      



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