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Markov Chains

Author : Pierre Bremaud

Publisher : Springer Science & Business Media

Page : 456 pages

File Size : 33,63 MB

Release : 2013-03-09

Category : Mathematics

ISBN : 1475731248

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Book Description

Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to the borders of contemporary research. Examples are from a wide range of domains, including operations research and electrical engineering. Researchers and students in these areas as well as in physics, biology and the social sciences will find this book of interest.



Non-negative Matrices and Markov Chains

Author : E. Seneta

Publisher : Springer Science & Business Media

Page : 295 pages

File Size : 32,90 MB

Release : 2006-07-02

Category : Mathematics

ISBN : 0387327924

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Book Description

Since its inception by Perron and Frobenius, the theory of non-negative matrices has developed enormously and is now being used and extended in applied fields of study as diverse as probability theory, numerical analysis, demography, mathematical economics, and dynamic programming, while its development is still proceeding rapidly as a branch of pure mathematics in its own right. While there are books which cover this or that aspect of the theory, it is nevertheless not uncommon for workers in one or another branch of its development to be unaware of what is known in other branches, even though there is often formal overlap. One of the purposes of this book is to relate several aspects of the theory, insofar as this is possible. The author hopes that the book will be useful to mathematicians; but in particular to the workers in applied fields, so the mathematics has been kept as simple as could be managed. The mathematical requisites for reading it are: some knowledge of real-variable theory, and matrix theory; and a little knowledge of complex-variable; the emphasis is on real-variable methods. (There is only one part of the book, the second part of 55.5, which is of rather specialist interest, and requires deeper knowledge.) Appendices provide brief expositions of those areas of mathematics needed which may be less g- erally known to the average reader.



Non-Homogeneous Markov Chains and Systems

Author : P.-C.G. Vassiliou

Publisher : CRC Press

Page : 607 pages

File Size : 21,12 MB

Release : 2022-12-21

Category : Mathematics

ISBN : 135198070X

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Book Description

Non-Homogeneous Markov Chains and Systems: Theory and Applications fulfills two principal goals. It is devoted to the study of non-homogeneous Markov chains in the first part, and to the evolution of the theory and applications of non-homogeneous Markov systems (populations) in the second. The book is self-contained, requiring a moderate background in basic probability theory and linear algebra, common to most undergraduate programs in mathematics, statistics, and applied probability. There are some advanced parts, which need measure theory and other advanced mathematics, but the readers are alerted to these so they may focus on the basic results. Features A broad and accessible overview of non-homogeneous Markov chains and systems Fills a significant gap in the current literature A good balance of theory and applications, with advanced mathematical details separated from the main results Many illustrative examples of potential applications from a variety of fields Suitable for use as a course text for postgraduate students of applied probability, or for self-study Potential applications included could lead to other quantitative areas The book is primarily aimed at postgraduate students, researchers, and practitioners in applied probability and statistics, and the presentation has been planned and structured in a way to provide flexibility in topic selection so that the text can be adapted to meet the demands of different course outlines. The text could be used to teach a course to students studying applied probability at a postgraduate level or for self-study. It includes many illustrative examples of potential applications, in order to be useful to researchers from a variety of fields.



Lectures on the Coupling Method

Author : Torgny Lindvall

Publisher : Courier Corporation

Page : 292 pages

File Size : 48,7 MB

Release : 2012-08-15

Category : Mathematics

ISBN : 048615324X

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Book Description

Practical and easy-to-use reference progresses from simple to advanced topics, covering, among other topics, renewal theory, Markov chains, Poisson approximation, ergodicity, and Strassen's theorem. 1992 edition.



Basics of Applied Stochastic Processes

Author : Richard Serfozo

Publisher : Springer Science & Business Media

Page : 452 pages

File Size : 35,12 MB

Release : 2009-01-24

Category : Mathematics

ISBN : 3540893326

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Book Description

Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes.



Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author : Marie-Jeanne Lesot

Publisher : Springer Nature

Page : 816 pages

File Size : 27,86 MB

Release : 2020-06-05

Category : Computers

ISBN : 3030501434

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Book Description

This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.



Models for Quantifying Risk, Sixth Edition

Author : Stephen J. Camilli, ASA

Publisher : ACTEX Publications

Page : 538 pages

File Size : 33,49 MB

Release : 2014-06-24

Category : Business & Economics

ISBN : 1625423470

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Book Description

This book is used in many university courses for SOA Exam MLC preparation. The Fifth Edition is the official reference for CAS Exam LC. The Sixth Edition of this textbook presents a variety of stochastic models for the actuary to use in undertaking the analysis of risk. It is designed to be appropriate for use in a two or three semester university course in basic actuarial science. It was written with the SOA Exam MLC and CAS Exam LC in mind. Models are evaluated in a generic form with life contingencies included as one of many applications of the science. Students will find this book to be a valuable reference due to its easy-to-understand explanations and end-of-chapter exercises. In 2013 the Society of Actuaries announced a change to Exam MLC's format, incorporating 60% written answer questions and new standard notation and terminology to be used for the exam. There are several areas of expanded content in the Sixth Edition due to these changes. Six important changes to the Sixth Edition: WRITTEN-ANSWER EXAMPLES This edition offers additional written-answer examples in order to better prepare the reader for the new SOA eam format. NOTATION AND TERMINOLOGY CONFORMS TO EXAM MLC MQR 6 fully incorporates all standard notation and terminology for exam MLC, as detailed by the SOA in their document Notation and Terminology Used on Exam MLC. MULTI-STATE MODELS Extension of multi-state model representationt to almost all topics covered in the text. FOCUS ON NORTH AMERICAN MARKET AND ACTUARIAL PROFESSION This book is written specifically for the multi-disciplinary needs of the North American Market. This is reflected in both content and terminology. PROFIT TESTING, PARTICIPATING INSURANCE, AND UNIVERSAL LIFE MQR 6 contains an expanded treatment of these topics. THIELE'S EQUATION Additional applications of this important equation are presented, to more fully prepare the reader for exam day. A separate solutions manual with detailed solutions to all of the text exercises is also available. Please see the Related Items Tab for a direct link I selected Models for Quantifying Risk as the text for my class. Given that the syllabus had changed quite dramatically from prior years, I was looking for a text that would cover all the material in the new syllabus in a way that was rigorous, easy to understand, and would prepare students for the May 2012 MLC exam. To me, the text with the accompanying solutions manual does precisely that. --Jay Vadiveloo, Ph.D., FSA, MAAA, CFA, Math Department, University of Connecticut I found that the exposition of the material is thorough while the concepts are readily accessible and well illustrated with examples. The book was an invaluable source of practice problems when I was preparing for the Exam MLC. Studying from it enabled me to pass this exam." -- Dmitry Glotov, Math Department, University of Connecticut "This book is extremely well written and structured." -- Kate Li, Student, University of Connecticut "Overall, the text is thorough, understandable, and well-organized. The clear exposition and excellent use of examples will benefit the student and help her avoid 'missing the forest for the trees'. I was impressed by the quality and quantity of examples and exercises throughout the text; students will find this collection of problems sorted by topic valuable for their exam preparation. Overall, I strongly recommend the book." -- Kristin Moore, Ph.D., ASA, University of Michigan



Proceedings of the Seventh Conference on Probability Theory

Author : Marius Iosifescu

Publisher : Walter de Gruyter GmbH & Co KG

Page : 676 pages

File Size : 50,71 MB

Release : 2020-05-18

Category : Mathematics

ISBN : 3112314034

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Book Description

No detailed description available for "Proceedings of the Seventh Conference on Probability Theory".



Hands-On Markov Models with Python

Author : Ankur Ankan

Publisher : Packt Publishing Ltd

Page : 172 pages

File Size : 35,92 MB

Release : 2018-09-27

Category : Computers

ISBN : 1788629337

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Book Description

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn Key FeaturesBuild a variety of Hidden Markov Models (HMM)Create and apply models to any sequence of data to analyze, predict, and extract valuable insightsUse natural language processing (NLP) techniques and 2D-HMM model for image segmentationBook Description Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone. Once you’ve covered the basic concepts of Markov chains, you’ll get insights into Markov processes, models, and types with the help of practical examples. After grasping these fundamentals, you’ll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you’ll explore the Bayesian approach of inference and learn how to apply it in HMMs. In further chapters, you’ll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You’ll also learn to apply HMM to image processing using 2D-HMM to segment images. Finally, you’ll understand how to apply HMM for reinforcement learning (RL) with the help of Q-Learning, and use this technique for single-stock and multi-stock algorithmic trading. By the end of this book, you will have grasped how to build your own Markov and hidden Markov models on complex datasets in order to apply them to projects. What you will learnExplore a balance of both theoretical and practical aspects of HMMImplement HMMs using different datasets in Python using different packagesUnderstand multiple inference algorithms and how to select the right algorithm to resolve your problemsDevelop a Bayesian approach to inference in HMMsImplement HMMs in finance, natural language processing (NLP), and image processingDetermine the most likely sequence of hidden states in an HMM using the Viterbi algorithmWho this book is for Hands-On Markov Models with Python is for you if you are a data analyst, data scientist, or machine learning developer and want to enhance your machine learning knowledge and skills. This book will also help you build your own hidden Markov models by applying them to any sequence of data. Basic knowledge of machine learning and the Python programming language is expected to get the most out of the book



Non-homogeneous Random Walks

Author : Mikhail Menshikov

Publisher : Cambridge University Press

Page : 385 pages

File Size : 33,58 MB

Release : 2016-12-22

Category : Mathematics

ISBN : 1316867366

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Book Description

Stochastic systems provide powerful abstract models for a variety of important real-life applications: for example, power supply, traffic flow, data transmission. They (and the real systems they model) are often subject to phase transitions, behaving in one way when a parameter is below a certain critical value, then switching behaviour as soon as that critical value is reached. In a real system, we do not necessarily have control over all the parameter values, so it is important to know how to find critical points and to understand system behaviour near these points. This book is a modern presentation of the 'semimartingale' or 'Lyapunov function' method applied to near-critical stochastic systems, exemplified by non-homogeneous random walks. Applications treat near-critical stochastic systems and range across modern probability theory from stochastic billiards models to interacting particle systems. Spatially non-homogeneous random walks are explored in depth, as they provide prototypical near-critical systems.