Stochastic Models Analysis And Applications
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Stochastic Models Analysis And Applications
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Author : B. R. Bhat
language : en
Publisher: New Age International
Release Date : 2004
Stochastic Models Analysis And Applications written by B. R. Bhat and has been published by New Age International this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematical statistics categories.
The Book Presents A Systematic Exposition Of The Basic Theory And Applications Of Stochastic Models.Emphasising The Modelling Rather Than Mathematical Aspects Of Stochastic Processes, The Book Bridges The Gap Between The Theory And Applications Of These Processes.The Basic Building Blocks Of Model Construction Are Explained In A Step By Step Manner, Starting From The Simplest Model Of Random Walk And Proceeding Gradually To More Complicated Models. Several Examples Are Given Throughout The Text To Illustrate Important Analytical Properties As Well As To Provide Applications.The Book Also Includes A Detailed Chapter On Inference For Stochastic Processes. This Chapter Highlights Some Of The Recent Developments In The Subject And Explains Them Through Illustrative Examples.An Important Feature Of The Book Is The Complements And Problems Section At The End Of Each Chapter Which Presents (I) Additional Properties Of The Model, (Ii) Extensions Of The Model, And (Iii) Applications Of The Model To Different Areas.With All These Features, This Is An Invaluable Text For Post-Graduate Students Of Statistics, Mathematics And Operation Research.
Stochastic Models
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Author : B. R. BHAT
language : en
Publisher:
Release Date : 2019
Stochastic Models written by B. R. BHAT and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Mathematical statistics categories.
Stochastic Models Statistics And Their Applications
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Author : Ansgar Steland
language : en
Publisher: Springer Nature
Release Date : 2019-10-15
Stochastic Models Statistics And Their Applications written by Ansgar Steland and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-15 with Mathematics categories.
This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
Mathematical Modeling
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Author : Sandip Banerjee
language : en
Publisher: CRC Press
Release Date : 2021-12-05
Mathematical Modeling written by Sandip Banerjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-05 with Mathematics categories.
Mathematical Modeling: Models, Analysis and Applications, Second Edition introduces models of both discrete and continuous systems. This book is aimed at newcomers who desires to learn mathematical modeling, especially students taking a first course in the subject. Beginning with the step-by-step guidance of model formulation, this book equips the reader about modeling with difference equations (discrete models), ODE’s, PDE’s, delay and stochastic differential equations (continuous models). This book provides interdisciplinary and integrative overview of mathematical modeling, making it a complete textbook for a wide audience. A unique feature of the book is the breadth of coverage of different examples on mathematical modelling, which include population models, economic models, arms race models, combat models, learning model, alcohol dynamics model, carbon dating, drug distribution models, mechanical oscillation models, epidemic models, tumor models, traffic flow models, crime flow models, spatial models, football team performance model, breathing model, two neuron system model, zombie model and model on love affairs. Common themes such as equilibrium points, stability, phase plane analysis, bifurcations, limit cycles, period doubling and chaos run through several chapters and their interpretations in the context of the model have been highlighted. In chapter 3, a section on estimation of system parameters with real life data for model validation has also been discussed. Features Covers discrete, continuous, spatial, delayed and stochastic models. Over 250 illustrations, 300 examples and exercises with complete solutions. Incorporates MATHEMATICA® and MATLAB®, each chapter contains Mathematica and Matlab codes used to display numerical results (available at CRC website). Separate sections for Projects. Several exercise problems can also be used for projects. Presents real life examples of discrete and continuous scenarios. The book is ideal for an introductory course for undergraduate and graduate students, engineers, applied mathematicians and researchers working in various areas of natural and applied sciences.
An Introduction To Stochastic Modeling
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Author : Howard M. Taylor
language : en
Publisher: Academic Press
Release Date : 2014-05-10
An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.
An Introduction to Stochastic Modeling 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.
Stochastic Models In The Life Sciences And Their Methods Of Analysis
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Author : Frederic Y M Wan
language : en
Publisher: World Scientific
Release Date : 2019-08-29
Stochastic Models In The Life Sciences And Their Methods Of Analysis written by Frederic Y M Wan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-29 with Mathematics categories.
'… the volume is impressively accessible. The result is a book that is valuable and approachable for biologists at all levels, including those interested in deepening their skills in mathematical modeling and those who seek an overview to aid them in communicating with collaborators in mathematics and statistics. The former group of readers may especially appreciate the first chapter, an introduction to key concepts in probability, and the set of ten assignments provided as an appendix.'CHOICEBiological processes are evolutionary in nature and often evolve in a noisy environment or in the presence of uncertainty. Such evolving phenomena are necessarily modeled mathematically by stochastic differential/difference equations (SDE), which have been recognized as essential for a true understanding of many biological phenomena. Yet, there is a dearth of teaching material in this area for interested students and researchers, notwithstanding the addition of some recent texts on stochastic modelling in the life sciences. The reason may well be the demanding mathematical pre-requisites needed to 'solve' SDE.A principal goal of this volume is to provide a working knowledge of SDE based on the premise that familiarity with the basic elements of a stochastic calculus for random processes is unavoidable. Through some SDE models of familiar biological phenomena, we show how stochastic methods developed for other areas of science and engineering are also useful in the life sciences. In the process, the volume introduces to biologists a collection of analytical and computational methods for research and applications in this emerging area of life science. The additions broaden the available tools for SDE models for biologists that have been limited by and large to stochastic simulations.
Introduction To Modeling And Analysis Of Stochastic Systems
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Author : V. G. Kulkarni
language : en
Publisher: Springer
Release Date : 2010-11-03
Introduction To Modeling And Analysis Of Stochastic Systems written by V. G. Kulkarni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-03 with Mathematics categories.
This is an introductory-level text on stochastic modeling. It is suited for undergraduate students in engineering, operations research, statistics, mathematics, actuarial science, business management, computer science, and public policy. It employs a large number of examples to teach the students to use stochastic models of real-life systems to predict their performance, and use this analysis to design better systems. The book is devoted to the study of important classes of stochastic processes: discrete and continuous time Markov processes, Poisson processes, renewal and regenerative processes, semi-Markov processes, queueing models, and diffusion processes. The book systematically studies the short-term and the long-term behavior, cost/reward models, and first passage times. All the material is illustrated with many examples, and case studies. The book provides a concise review of probability in the appendix. The book emphasizes numerical answers to the problems. A collection of MATLAB programs to accompany the this book can be downloaded from http://www.unc.edu/~vkulkarn/Maxim/maxim.zip. A graphical user interface to access the above files can be downloaded from http://www.unc.edu/~vkulkarn/Maxim/maximgui.zip . The second edition incorporates several changes. First its title reflects the changes in content: the chapters on design and control have been removed. The book now contains several case studies that teach the design principles. Two new chapters have been added. The new chapter on Poisson processes gives more attention to this important class of stochastic processes than the first edition did. The new chapter on Brownian motion reflects its increasing importance as an appropriate model for a variety of real-life situations, including finance.
An Introduction To Stochastic Modeling
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Author : Mark Pinsky
language : en
Publisher: Academic Press
Release Date : 2010-11-18
An Introduction To Stochastic Modeling written by Mark Pinsky and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-18 with Mathematics categories.
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
Nbs Special Publication
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Author :
language : en
Publisher:
Release Date : 1970
Nbs Special Publication written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with Weights and measures categories.
Stochastic Models Information Theory And Lie Groups Volume 2
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Author : Gregory S. Chirikjian
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-11-15
Stochastic Models Information Theory And Lie Groups Volume 2 written by Gregory S. Chirikjian and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-15 with Mathematics categories.
This unique two-volume set presents the subjects of stochastic processes, information theory, and Lie groups in a unified setting, thereby building bridges between fields that are rarely studied by the same people. Unlike the many excellent formal treatments available for each of these subjects individually, the emphasis in both of these volumes is on the use of stochastic, geometric, and group-theoretic concepts in the modeling of physical phenomena. Stochastic Models, Information Theory, and Lie Groups will be of interest to advanced undergraduate and graduate students, researchers, and practitioners working in applied mathematics, the physical sciences, and engineering. Extensive exercises, motivating examples, and real-world applications make the work suitable as a textbook for use in courses that emphasize applied stochastic processes or differential geometry.