Stochastic Modeling of AIDS Epidemiology and HIV Pathogenesis PDF Download

Author: W. Y. Tan
Publisher: World Scientific
ISBN: 9789810241223
Category : Mathematics
Languages : en
Pages : 458

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Book Description
This book discusses systematically treatment on the development of stochastic, statistical and state space models of the HIV epidemic and of HIV pathogenesis in HIV-infected individuals, and presents the applications of these models. The book is unique in several ways: (1) it uses stochastic difference and differential equations to present the stochastic models of the HIV epidemic and HIV pathogenesis; in this sense, the deterministic models are considered as special cases when the numbers of different type of people or cells are very large (2) it provides, a critical analysis of deterministic and statistical models in the literature; (3) it develops state space models by combining stochastic models and statistical models; and (4) it provides a detailed discussion on the pros and cons of the different modeling approaches. This book is the first to introduce state space models for the HIV epidemic. It is also the first to develop stochastic models and state space models for the HIV pathogenesis in HIV-infected individuals.

Author: Quan-Lin Li
Publisher: Springer Nature
ISBN: 981150864X
Category : Computers
Languages : en
Pages : 497

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Book Description
This book is dedicated to Jinhua Cao on the occasion of his 80th birthday. Jinhua Cao is one of the most famous reliability theorists. His main contributions include: published over 100 influential scientific papers; published an interesting reliability book in Chinese in 1986, which has greatly influenced the reliability of education, academic research and engineering applications in China; initiated and organized Reliability Professional Society of China (the first part of Operations Research Society of China) since 1981. The high admiration that Professor Cao enjoys in the reliability community all over the world was witnessed by the enthusiastic response of each contributor in this book. The contributors are leading researchers with diverse research perspectives. The research areas of the book iclude a broad range of topics related to reliability models, queueing theory, manufacturing systems, supply chain finance, risk management, Markov decision processes, blockchain and so forth. The book consists of a brief Preface describing the main achievements of Professor Cao; followed by congratulations from Professors Way Kuo and Wei Wayne Li, and by Operations Research Society of China, and Reliability Professional Society of China; and further followed by 25 articles roughly grouped together. Most of the articles are written in a style understandable to a wide audience. This book is useful to anyone interested in recent developments in reliability, network security, system safety, and their stochastic modeling and analysis.

Author: Herold G. Dehling
Publisher: Elsevier
ISBN: 9780080548975
Category : Mathematics
Languages : en
Pages : 290

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Book Description
There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. Introduction to stochastic process modelling as an alternative modelling technique Shows how stochastic modelling may be succesful where the traditional technique fails Overview of stochastic modelling in process technology in the research literature Illustration of the principle by a wide range of practical examples In-depth and self-contained discussions Points the way to both mathematical and technological research in a new, rewarding field

Author: J. George Shanthikumar
Publisher: Springer Science & Business Media
ISBN: 1461503736
Category : Business & Economics
Languages : en
Pages : 413

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Book Description
This volume originates from two workshops, both focusing on themes that are reflected in the title of the volume. The first workshop took place at Eindhoven University of Technology, April 24-26, 2001, on the occasion of the University granting a doctorate honoris causa to Profes sor John A. Buzacott. The second workshop was held on June 15, 2002 at Cornell University (preceding the annual INFORMSjMSOM Confer ence), honoring John's retirement and his lifetime contributions. Each of the two workshops consisted of about a dozen technical presentations. The objective of the volume, however, is not to simply publish the proceedings of the two workshops. Rather, our objective is to put to gether a select set of articles, each organized into a well-written chapter, focusing on a timely topic. Collected into a single volume, these chapters aim to serve as a useful reference for researchers and practitioners alike, and also as reading materials for graduate courses or seminars.

Author: Radek Erban
Publisher: Cambridge University Press
ISBN: 1108498124
Category : Mathematics
Languages : en
Pages : 321

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Book Description
Practical introduction for advanced undergraduate or beginning graduate students of applied mathematics, developed at the University of Oxford.

Author: Mariano J Valderrama Bonnet
Publisher: World Scientific
ISBN: 9814550701
Category :
Languages : en
Pages : 326

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Book Description
This volume contains a selection of papers on recent developments in fields such as stochastic processes, multivariate data analysis and stochastic models in operations research, earth and life sciences and information theory, from an applicative perspective. Some of them have been extracted from lectures given at the Department of Statistics and Operations Research at the University of Granada for the past two years (Kai Lai Chung and Marcel F Neuts, among others). All the papers have been carefully selected and revised.

Author: Khalid Al-Begain
Publisher: Springer
ISBN: 3642022057
Category : Computers
Languages : en
Pages : 401

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Book Description
This book constitutes the refereed proceedings of the 16th International Conference on Analytical and Stochastic Modeling Techniques and Applications, ASMTA 2009, held in Madrid, Spain, in June 2009 in conjunction with ECMS 2009, the 23nd European Conference on Modeling and Simulation. The 27 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on telecommunication networks; wireless & mobile networks; simulation; quueing systems & distributions; queueing & scheduling in telecommunication networks; model checking & process algebra; performance & reliability analysis of various systems.

Author: Mark Pinsky
Publisher: Academic Press
ISBN: 0123814170
Category : Mathematics
Languages : en
Pages : 584

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Book Description
Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Fourth Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems. New to this edition: Realistic applications from a variety of disciplines integrated throughout the text, including more biological applications Plentiful, completely updated problems Completely updated and reorganized end-of-chapter exercise sets, 250 exercises with answers New chapters of stochastic differential equations and Brownian motion and related processes Additional sections on Martingale and Poisson process Realistic applications from a variety of disciplines integrated throughout the text Extensive end of chapter exercises sets, 250 with answers Chapter 1-9 of the new edition are identical to the previous edition New! Chapter 10 - Random Evolutions New! Chapter 11- Characteristic functions and Their Applications

Author: Francisco J. Samaniego
Publisher: CRC Press
ISBN: 1466560479
Category : Mathematics
Languages : en
Pages : 622

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Book Description
Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well

Author: Howard M. Taylor
Publisher: Academic Press
ISBN: 1483220443
Category : Mathematics
Languages : en
Pages : 578

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Book Description
An Introduction to Stochastic Modeling, Revised Edition provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.