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Autor(en): 
  • Nitis Mukhopadhyay
  • de Silva Basil M.
  • Sequential Methods and Their Applications 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2008  
    Genre:  Schulbücher 
     
    Bayesian data analysis / confidence interval methods / experimental design statistics / Mathematics / MATHEMATICS / General / multistage estimation / Nonparametric Inference / sequential analysis for real data applications
    ISBN:  9781584881025 
    EAN-Code: 
    9781584881025 
    Verlag:  Taylor and Francis 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D 40 mm 
    Gewicht:  975 gr 
    Seiten:  512 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come Alive Taking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas. The book first explores fixed sample size, sequential probability ratio, and nonparametric tests. It then presents numerous multistage estimation methods for fixed-width confidence interval as well as minimum and bounded risk problems. The book also describes multistage fixed-size confidence region methodologies, selection methodologies, and Bayesian estimation. Through diverse applications, each chapter provides valuable approaches for performing statistical experiments and facilitating real data analysis. Functional in a variety of statistical problems, the authors' interactive computer programs show how the methodologies discussed can be implemented in data analysis. Each chapter offers examples of input, output, and their interpretations. Available online, the programs provide the option to save some parts of an output so readers can revisit computer-generated data for further examination with exploratory data analysis. Through this book and its computer programs, readers will better understand the methods of sequential analysis and be able to use them in real-world settings.

      



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