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Applied Probability and Stochastic - Hardcover, by Beichelt Frank - Good

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Book Title
Applied Probability and Stochastic Processes
ISBN
9781482257649
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關於產品

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1482257645
ISBN-13
9781482257649
eBay Product ID (ePID)
219131839

Product Key Features

Number of Pages
562 Pages
Language
English
Publication Name
Applied Probability and Stochastic Processes
Subject
Probability & Statistics / Stochastic Processes, Operations Research, General, Probability & Statistics / Bayesian Analysis
Publication Year
2016
Type
Textbook
Author
Frank Beichelt
Subject Area
Mathematics, Business & Economics
Format
Hardcover

Dimensions

Item Height
1.4 in
Item Weight
32.9 Oz
Item Length
9.6 in
Item Width
6.5 in

Additional Product Features

Edition Number
2
Intended Audience
College Audience
LCCN
2016-429382
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
519.23
Table Of Content
PROBABILITY THEORY RANDOM EVENTS AND THEIR PROBABILITIES RANDOM EXPERIMENTS RANDOM EVENTS PROBABILITY CONDITIONAL PROBABILITY AND INDEPENDENCE OF RANDOM EVENTS ONE-DIMENSIONAL RANDOM VARIABLES MOTIVATION AND TERMINOLOGY DISCRETE RANDOM VARIABLES CONTINUOUS RANDOM VARIABLES MIXTURES OF RANDOM VARIABLES GENERATING FUNCTIONS MULTIDIMENSIONAL RANDOM VARIABLES TWO-DIMENSIONAL RANDOM VARIABLES n -DIMENSIONAL RANDOM VARIABLES FUNCTIONS OF RANDOM VARIABLES FUNCTIONS OF ONE RANDOM VARIABLE FUNCTIONS OF SEVERAL RANDOM VARIABLES SUMS OF RANDOM VARIABLES INEQUALITIES AND LIMIT THEOREMS INEQUALITIES LIMIT THEOREMS STOCHASTIC PROCESSES BASICS OF STOCHASTIC PROCESSES MOTIVATION AND TERMINOLOGY CHARACTERISTICS AND EXAMPLES CLASSIFICATION OF STOCHASTIC PROCESSES TIME SERIES IN DISCRETE TIME RANDOM POINT PROCESSES BASIC CONCEPTS POISSON PROCESSES RENEWAL PROCESSES DISCRETE - TIME MARKOV CHAINS FOUNDATIONS AND EXAMPLES CLASSIFICATION OF STATES LIMIT THEOREMS AND STATIONARY DISTRIBUTION BIRTH AND DEATH PROCESSES DISCRETE-TIME BRANCHING PROCESSES CONTINUOUS-TIME MARKOV CHAINS BASIC CONCEPTS AND EXAMPLES TRANSITION PROBABILITIES AND RATES STATIONARY STATE PROBABILITIES SOJOURN TIMES IN PROCESS STATES CONSTRUCTION OF MARKOV SYSTEMS BIRTH AND DEATH PROCESSES APPLICATIONS TO QUEUEING MODELS SEMI-MARKOV CHAINS MARTINGALES DISCRETE-TIME MARTINGALES CONTINUOUS-TIME MARTINGALES BROWNIAN MOTION INTRODUCTION PROPERTIES OF THE BROWNIAN MOTION MULTIDIMENSIONAL AND CONDITIONAL DISTRIBUTIONS FIRST PASSAGE TIMES TRANSFORMATIONS OF THE BROWNIAN MOTION SPECTRAL ANALYSIS OF STATIONARY PROCESSES FOUNDATIONS PROCESSES WITH DISCRETE SPECTRUM PROCESSES WITH CONTINUOUS SPECTRUM REFERENCES INDEX Exercises appear at the end of each chapter.
Edition Description
Revised edition,New Edition
Synopsis
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.
LC Classification Number
QA274.B399 2016

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