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Probability: Interpretation, Theory and Applications $165.00
Editors: Yuriy S. Shmaliy (Guanajuato University, Salamanca, Gto, Mexico)
Book Description:
This book is a collective work made by various authors well-recognized owing to their appreciable contributions to the theory and applications of probability. Both mathematical and engineering aspects of probability outline its framework. Readers can find here several timely topics such as risk theory and applications, Laplace distributions which describe the heavy-tailed noise, Poisson sums having applications in business and engineering, Markov chains investigations and approximations, Berstein-Hoeffding-type exponential inequalities useful for proving limiting theorems, Bayesian computational methods, as well as a modern view on sampling and reconstruction of Gaussian and non-Gaussian random processes. (Imprint: Nova)

Table of Contents:
Preface

Chapter 1 – Risk Theory in Actuarial Science
(Dimitrios G. Konstantinides, Department of Statistics and Actuarial Financial Mathematics, University of the Aegean, Mytilene, Greece)

Chapter 2 – Multivariate Models Connected with Poisson Sums and Maxima of Exponentials
(Anna K. Panorska, Department of Mathematics and Statistics,
University of Nevada, Reno, USA)

Chapter 3 – Laplace Probability Distributions and Related Stochastic Processes
(Tomasz J. Kozubowski, Department of Mathematics and Statistics,
University of Nevada, Reno, USA; Krzysztof Podgorski, Centre for Mathematical Sciences, Mathematical Statistics,
Lund University, Lund, Sweden)

Chapter 4 – Markov Chain Approximation for Stochastic Control and Games
(Qingshuo Song, Department of Mathematics, City University of Hong Kong, Hong Kong, China)

Chapter 5 – A Random Time Horizon Optimal Stopping Problem
(Huiling Le, School of Mathematical Sciences, University of Nottingham, UK; Chudong Wang, School of Pharmacy, University of Nottingham, Nottingham, UK)

Chapter 6 – Dendrogram Representation of Stochastic Clustering
(Vahid Partovi Nia, Department of Mathematics and Industrial Engineering, Ecole Polytechnique Montreal, Montreal, Canada
David Stephens, Department of Mathematics and Statistics,
McGill University, Montreal, Canada)

Chapter 7 – Berstein-Hoeffding Type Exponential Inequalities and Strong Laws of Large Numbers
(Guo-dong Xing, Department of Mathematics, Hefei Normal University, Hefei, China; Shan-chao Yang, Department of Mathematics
Guangxi Normal University, Guilin, Guangxi, China)

Chapter 8 – Bayesian Computational Methods for Meta-Analysis of Gene Expression Studies
(Erin M. Conlon, Department of Mathematics and Statistics,
University of Massachusetts, Amherst, USA; Joon J. Song, Department of Mathematics, University of Arkansas, Fayetteville, USA)

Chapter 9 – Sampling – Reconstruction Procedures of Gaussian Process Realizations
(Vladimir Kazakov, Department of Telecommunications Engineering,
National Polytechnic Institute, Zacatenco, Mexico-City, Mexico)

Chapter 10 – Sampling – Reconstruction Procedures of Non-Gaussian Process Realizations
(Vladimir Kazakov, Department of Telecommunications Engineering,
National Polytechnic Institute, Zacatenco, Mexico-City, Mexico)

Chapter 11 – Statistical Inference for Elliptically Contoured Distributions
(Amadou Sarr, Department of Mathematics and Statistics,
McMaster University, Hamilton, Canada)

Index

   Series:
      Mathematics Research Developments
   Binding: ebook
   Pub. Date: 2012
   Pages: 7 x 10 (NBC - C)
   ISBN: 978-1-62100-305-2
   Status: AV
  
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