Best Reference Books – Introduction to Stochastic Models

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We have compiled the list of Top 10 Best Reference Books on Introduction To Stochastic Models subject. These books are used by students of top universities, institutes and colleges. Here is the full list of top 10 best books on Introduction To Stochastic Models along with reviews.

Kindly note that we have put a lot of effort into researching the best books on Introduction To Stochastic Models subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Introduction To Stochastic Models" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.

1. “Probability and Random Processes” by G R Grimmett and D R Stizaker

Book Review: This book provides a rigorous introduction to the field of probability theory and discusses the random processes in detail. The book basically has 4 main aims which are providing the concepts of basic probability in a straightforward manner, random processes discussion with examples, covering many important topics and impart the beginner with advanced work. The book contains newer chapters on sampling, markov chain, monte carlo, coupling, geometric probability, queuing networks, stochastic calculus and many more.

2. “An Introduction to Probability Theory and its Applications” by W Feller

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“An Introduction to Probability Theory and its Applications” Book Review: The book starts with the background and nature of probability theory, Moving further the topics like sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, and stochastic processes are described in detail. To give better practical knowledge and relatable content to the readers many real-world applications of probability theory are also included in this book.

3. “Introduction to Stochastic Processes” by E Cinlar

“Introduction to Stochastic Processes” Book Review: The book is highly recommended for the students, professionals and researchers who want to gain knowledge in the field of ‘Stochastic Processes’. All the basic concepts and theory of the preceding field is described in this book. It covers topics like probability spaces and random variables, expectations and independence, Bernoulli processes and sums of independent random variables, Poisson processes, Markov chains and processes, and renewal theory. The content of the book is precise, clear, and well-structured. It features many exercises, examples and illustrations.

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4. “Stochastic Modeling and the Theory of Queues” by R W Wolff

Book Review: This book contains up-to-date information on applied stochastic processes and queuing theory with major stress on time averages. The book also demonstrates the concepts of priorities, queue pooling, bottlenecks and many more. This book is suitable for graduate courses in queuing theory in the field of operations research, computer science, statistics and industrial engineering. The book also deals with queues and stochastic processes. It also contains details about renewal theory, renewal theorems and regenerative processes.

5. “Introduction To Stochastic Models” by Nikolaos Limnios

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“Introduction To Stochastic Models” Book Review: The book will be useful for students and researchers in applied sciences or anyone seeking an introduction to ‘Stochastic Models’. This book is an informative text, which describes how the stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. The book contains topics like markov and semi-markov models, poisson, renewal processes, branching processes, ehrenfest models, genetic models, optimal stopping, reliability, reservoir theory, storage models, and queuing systems.

6. “INTRODUCTION TO STOCHASTIC MODELS” by D’Marreio Brooks
7. “An Introduction to Differential Equations: Stochastic Modeling, Methods and Analysis” by Anil G Ladde and G S Ladde

“An Introduction to Differential Equations: Stochastic Modeling, Methods and Analysis” Book Review: The book is basically for undergraduate and graduate students of stochastic modeling and applied mathematics courses, but will also be helpful for the researchers of these courses. It features topics like elements of stochastic processes and ito–doob stochastic calculus, first-order differential equations, first-order nonlinear differential equations, first-order systems of linear differential equations, higher-order differential equations. The book contains all the important concepts and methodologies of the given topics.

8. “An Introduction to Stochastic Modeling” by Mark A Pinsky and Samuel Karlin

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“An Introduction to Stochastic Modeling” Book Review: The book can be referred by the students for their undergraduate and graduate courses related to stochastic processes and modeling. The book starts with introduction to stochastic modeling, and further describes standard concepts and methods of stochastic modeling. Many real-life and biological applications of stochastic processes are highlighted in this book. Each chapter is followed by exercises for self-assessment. The content of this book is fully updated, thus containing new chapters and problems.

9. “Elementary Introduction to Stochastic Interest Rate Modeling” by Nicolas Privault

“Elementary Introduction to Stochastic Interest Rate Modeling” Book Review: The book can be referred by advanced undergraduate and graduate level students. It is majorly based on ‘interest rate modeling’ and ‘pricing of related derivatives’. The topics like stochastic interest rate models, standard short rate models, forward rate models, pricing of related derivatives, Bgm model, and an approach to its calibration are also covered in this book. The book also features a chapter on ‘credit risk’. Each chapter is ended with exercises along with their clear solutions.

10. “Introduction to Stochastic Networks” by Richard Serfozo

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“Introduction to Stochastic Networks” Book Review: The book is basically for graduate students and researchers in engineering, science and mathematics. It starts with a description of Jackson networks and then explains spatial queuing systems. It describes topics like basic stochastic network processes, reversible markov processes, palm probabilities for stationary systems, little laws for queuing systems, and space-time Poisson processes. The book features expressions for the equilibrium probability distribution of the numbers of units at the stations. It also highlights real-analysis and recent developments in the stochastic networks.

People who are searching for Free downloads of books and free pdf copies of these top 10 books on Introduction To Stochastic Models – we would like to mention that we don’t have free downloadable pdf copies of these good books and one should look for free pdf copies from these Authors only if they have explicitly made it free to download and read them.

We have created a collection of best reference books on "Introduction To Stochastic Models" so that one can readily see the list of top books on "Introduction To Stochastic Models" and buy the books either online or offline.

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Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn | Youtube | Instagram | Facebook | Twitter