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Autor(en): 
  • Luca Martino
  • David Luengo
  • Joaquín Míguez
  • Independent Random Sampling Methods 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2018  
    Genre:  Schulbücher 
     
    Applications of Mathematics / B / Computer science—Mathematics / Economics, Mathematical / Finance & accounting / Mathematical theory of computation / Mathematics and Statistics / Mathematics of Computing / Maths for computer scientists / Probability & statistics / Probability and statistics / Quantitative Finance / Statistical Theory and Methods / Statistics / Statistics and Computing / Statistics and Computing/Statistics Programs
    ISBN:  9783319726335 
    EAN-Code: 
    9783319726335 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Statistics and Computing  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  606 gr 
    Seiten:  280 
    Illustration:  XII, 280 p. 55 illus., 52 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code.

    The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the links and interplay between ostensibly diverse techniques.


      
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