probability and stochastic modeling

Download Book Probability And Stochastic Modeling in PDF format. You can Read Online Probability And Stochastic Modeling here in PDF, EPUB, Mobi or Docx formats.

Probability And Stochastic Modeling

Author : Vladimir I. Rotar
ISBN : 9781420010992
Genre : Mathematics
File Size : 74. 63 MB
Format : PDF, ePub, Docs
Download : 409
Read : 631

Download Now

A First Course in Probability with an Emphasis on Stochastic Modeling Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitable for majors in mathematics and statistics as well as majors in computer science, economics, finance, and physics. The author offers two explicit options to teaching the material, which is reflected in "routes" designated by special "roadside" markers. The first route contains basic, self-contained material for a one-semester course. The second provides a more complete exposition for a two-semester course or self-study.

Concepts In Probability And Stochastic Modeling

Author : James J. Higgins
ISBN : UOM:39015033980346
Genre : Mathematics
File Size : 78. 46 MB
Format : PDF, ePub, Mobi
Download : 608
Read : 878

Download Now

This text stresses modern ideas, including simulation and interpretation of results. It focuses on the aspects of probability most relevant to applications, such as stochastic modeling, Markov chains, reliability, and queuing.

An Introduction To Stochastic Modeling

Author : Howard M. Taylor
ISBN : 9781483220444
Genre : Mathematics
File Size : 73. 76 MB
Format : PDF
Download : 474
Read : 617

Download Now

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.

Student Solutions Manual For Concepts In Probability And Stochastic Modeling

Author : James J. Higgins
ISBN : 0534231373
Genre : Probabilities
File Size : 22. 97 MB
Format : PDF, ePub
Download : 772
Read : 820

Download Now

This ground-breaking text stresses modern ideas, including simulation and interpretation of results. It focuses on aspects of probability most relevant to applied uses such as stochastic modeling, Markov chains, reliability, and queuing.

Stochastic Modeling

Author : Barry L. Nelson
ISBN : 9780486139944
Genre : Mathematics
File Size : 60. 93 MB
Format : PDF, Kindle
Download : 479
Read : 187

Download Now

Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.

Applied Probability And Stochastic Processes Second Edition

Author : Frank Beichelt
ISBN : 9781482257656
Genre : Business & Economics
File Size : 61. 62 MB
Format : PDF, Kindle
Download : 415
Read : 272

Download Now

Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. It covers the theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates applications through the analysis of numerous practical examples. The author draws on his 50 years of experience in the field to give your students a better understanding of probability theory and stochastic processes and enable them to use stochastic modeling in their work. New to the Second Edition Completely rewritten part on probability theory—now more than double in size New sections on time series analysis, random walks, branching processes, and spectral analysis of stationary stochastic processes Comprehensive numerical discussions of examples, which replace the more theoretically challenging sections Additional examples, exercises, and figures Presenting the material in a student-friendly, application-oriented manner, this non-measure theoretic text only assumes a mathematical maturity that applied science students acquire during their undergraduate studies in mathematics. Many exercises allow students to assess their understanding of the topics. In addition, the book occasionally describes connections between probabilistic concepts and corresponding statistical approaches to facilitate comprehension. Some important proofs and challenging examples and exercises are also included for more theoretically interested readers.

Identifiability In Stochastic Models

Author : Gerard Meurant
ISBN : 9780128015261
Genre : Mathematics
File Size : 35. 76 MB
Format : PDF, ePub, Mobi
Download : 541
Read : 1332

Download Now

The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of "characterization problems" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.

An Introduction To Probability And Stochastic Processes

Author : James L. Melsa
ISBN : 9780486490991
Genre : Mathematics
File Size : 80. 42 MB
Format : PDF, ePub, Mobi
Download : 491
Read : 1274

Download Now

Detailed coverage of probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Introduction To Matrix Analytic Methods In Stochastic Modeling

Author : G. Latouche
ISBN : 9780898714258
Genre : Mathematics
File Size : 51. 47 MB
Format : PDF, ePub
Download : 156
Read : 1015

Download Now

Presents the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner.

Stochastic Modeling

Author : Nicolas Lanchier
ISBN : 9783319500386
Genre : Mathematics
File Size : 51. 42 MB
Format : PDF, ePub, Mobi
Download : 589
Read : 843

Download Now

Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright –Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and MatlabTM.

Top Download:

Best Books