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Autor(en): 
  • Christian Houdré
  • Benjamin Arras
  • On Stein's Method for Infinitely Divisible Laws with Finite First Moment 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2019  
    Genre:  Schulbücher 
     
    C / Kolmogorov Distance / Mathematics and Statistics / Probabilities / Probability Theory / Probability Theory and Stochastic Processes / Rates of Convergence / Smooth Wasserstein Distance
    ISBN:  9783030150167 
    EAN-Code: 
    9783030150167 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  SpringerBriefs in Probability and Mathematical Statistics  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  192 gr 
    Seiten:  104 
    Illustration:  XI, 104 p. 1 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book focuses on quantitative approximation results for weak limit theorems when the target limiting law is infinitely divisible with finite first moment. Two methods are presented and developed to obtain such quantitative results. At the root of these methods stands a Stein characterizing identity discussed in the third chapter and obtained thanks to a covariance representation of infinitely divisible distributions. The first method is based on characteristic functions and Stein type identities when the involved sequence of random variables is itself infinitely divisible with finite first moment. In particular, based on this technique, quantitative versions of compound Poisson approximation of infinitely divisible distributions are presented. The second method is a general Stein's method approach for univariate selfdecomposable laws with finite first moment. Chapter 6 is concerned with applications and provides general upper bounds to quantify the rate of convergence in classicalweak limit theorems for sums of independent random variables. This book is aimed at graduate students and researchers working in probability theory and mathematical statistics.
      



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