An introduction to stochastic modeling / (Record no. 41713)

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066 ## - CHARACTER SETS PRESENT
Alternate G0 or G1 character set (S
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.23
Item number P658i
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Pinsky, Mark A.,
Dates associated with a name 1940-
Real World Object URI https://id.oclc.org/worldcat/entity/E39PBJhtbmDbqHGFYRpm98tqcP
245 13 - TITLE STATEMENT
Title An introduction to stochastic modeling /
Statement of responsibility, etc. Mark A. Pinsky, Samuel Karlin.
250 ## - EDITION STATEMENT
Edition statement 4th ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Amsterdam ;
-- Boston :
Name of publisher, distributor, etc. Academic Press,
Date of publication, distribution, etc. ©2011.
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 563 pages :
Other physical details illustrations ;
Dimensions 24 cm
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
500 ## - GENERAL NOTE
General note "Academic Press is an imprint of Elsevier."--Title page verso.
505 00 - FORMATTED CONTENTS NOTE
Miscellaneous information 1.
Title Introduction --
Miscellaneous information 2.
Title Conditional probability and conditional expectation --
Miscellaneous information 3.
Title Markov chains: introduction --
Miscellaneous information 4.
Title Long run behavior of Markov chains --
Miscellaneous information 5.
Title Poisson processes --
Miscellaneous information 6.
Title Continuous time Markov chains --
Miscellaneous information 7.
Title Renewal phenomena --
Miscellaneous information 8.
Title Brownian motion and related processes --
Miscellaneous information 9.
Title Queueing systems --
Miscellaneous information 10.
Title Random evolutions --
Miscellaneous information 11.
Title Characteristic functions and their applications.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Stochastic processes.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Markov-Kette
Source of heading or term gnd
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Poisson-Prozess
Source of heading or term gnd
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Karlin, Samuel,
Dates associated with a name 1923-2007.
Real World Object URI https://id.oclc.org/worldcat/entity/E39PBJhRyVgRBwtqgtXGtkXPQq
758 ## - RESOURCE IDENTIFIER
Relationship information has work:
Label An introduction to stochastic modelling (Text)
Real World Object URI https://id.oclc.org/worldcat/entity/E39PCGF9RgGxkhrDkXHB6hDM8y
Relationship https://id.oclc.org/worldcat/ontology/hasWork
880 00 - ALTERNATE GRAPHIC REPRESENTATION
Linkage 505-00/(S
a Machine generated contents note:
g 1.
t Introduction --
g 1.1.
t Stochastic Modeling --
g 1.1.1.
t Stochastic Processes --
g 1.2.
t Probability Review --
g 1.2.1.
t Events and Probabilities --
g 1.2.2.
t Random Variables --
g 1.2.3.
t Moments and Expected Values --
g 1.2.4.
t Joint Distribution Functions --
g 1.2.5.
t Sums and Convolutions --
g 1.2.6.
t Change of Variable --
g 1.2.7.
t Conditional Probability --
g 1.2.8.
t Review of Axiomatic Probability Theory --
g 1.3.
t Major Discrete Distributions --
g 1.3.1.
t Bernoulli Distribution --
g 1.3.2.
t Binomial Distribution --
g 1.3.3.
t Geometric and Negative Binominal Distributions --
g 1.3.4.
t Poisson Distribution --
g 1.3.5.
t Multinomial Distribution --
g 1.4.
t Important Continuous Distributions --
g 1.4.1.
t Normal Distribution --
g 1.4.2.
t Exponential Distribution --
g 1.4.3.
t Uniform Distribution --
g 1.4.4.
t Gamma Distribution --
g 1.4.5.
t Beta Distribution --
g 1.4.6.
t Joint Normal Distribution --
g 1.5.
t Some Elementary Exercises --
g 1.5.1.
t Tail Probabilities --
g 1.5.2.
t Exponential Distribution --
g 1.6.
t Useful Functions, Integrals, and Sums --
g 2.
t Conditional Probability and Conditional Expectation --
g 2.1.
t Discrete Case --
g 2.2.
t Dice Game Craps --
g 2.3.
t Random Sums --
g 2.3.1.
t Conditional Distributions: The Mixed Case --
g 2.3.2.
t Moments of a Random Sum --
g 2.3.3.
t Distribution of a Random Sum --
g 2.4.
t Conditioning on a Continuous Random Variable --
g 2.5.
t Martingales --
g 2.5.1.
t Definition --
g 2.5.2.
t Markov Inequality --
g 2.5.3.
t Maximal Inequality for Nonnegative Martingales --
g 3.
t Markov Chains: Introduction --
g 3.1.
t Definitions --
g 3.2.
t Transition Probability Matrices of a Markov Chain --
g 3.3.
t Some Markov Chain Models --
g 3.3.1.
t Inventory Model --
g 3.3.2.
t Ehrenfest Urn Model --
g 3.3.3.
t Markov Chains in Genetics --
g 3.3.4.
t Discrete Queueing Markov Chain --
g 3.4.
t First Step Analysis --
g 3.4.1.
t Simple First Step Analyses --
g 3.4.2.
t General Absorbing Markov Chain --
g 3.5.
t Some Special Markov Chains --
g 3.5.1.
t Two-State Markov Chain --
g 3.5.2.
t Markov Chains Defined by Independent Random Variables --
g 3.5.3.
t One-Dimensional Random Walks --
g 3.5.4.
t Success Runs --
g 3.6.
t Functionals of Random Walks and Success Runs --
g 3.6.1.
t General Random Walk --
g 3.6.2.
t Cash Management --
g 3.6.3.
t Success Runs Markov Chain --
g 3.7.
t Another Look at First Step Analysis --
g 3.8.
t Branching Processes --
g 3.8.1.
t Examples of Branching Processes --
g 3.8.2.
t Mean and Variance of a Branching Process --
g 3.8.3.
t Extinction Probabilities --
g 3.9.
t Branching Processes and Generating Functions --
g 3.9.1.
t Generating Functions and Extinction Probabilities --
g 3.9.2.
t Probability Generating Functions and Sums of Independent Random Variables --
g 3.9.3.
t Multiple Branching Processes --
g 4.
t Long Run Behavior of Markov Chains --
g 4.1.
t Regular Transition Probability Matrices --
g 4.1.1.
t Doubly Stochastic Matrices --
g 4.1.2.
t Interpretation of the Limiting Distribution --
g 4.2.
t Examples --
g 4.2.1.
t Including History in the State Description --
g 4.2.2.
t Reliability and Redundancy --
g 4.2.3.
t Continuous Sampling Plan --
g 4.2.4.
t Age Replacement Policies --
g 4.2.5.
t Optimal Replacement Rules --
g 4.3.
t Classification of States --
g 4.3.1.
t Irreducible Markov Chains --
g 4.3.2.
t Periodicity of a Markov Chain --
g 4.3.3.
t Recurrent and Transient States --
g 4.4.
t Basic Limit Theorem of Markov Chains --
g 4.5.
t Reducible Markov Chains --
g 5.
t Poisson Processes --
g 5.1.
t Poisson Distribution and the Poisson Process --
g 5.1.1.
t Poisson Distribution --
g 5.1.2.
t Poisson Process --
g 5.1.3.
t Nonhomogeneous Processes --
g 5.1.4.
t Cox Processes --
g 5.2.
t Law of Rare Events --
g 5.2.1.
t Law of Rare Events and the Poisson Process --
g 5.2.2.
t Proof of Theorem 5.3 --
g 5.3.
t Distributions Associated with the Poisson Process --
g 5.4.
t Uniform Distribution and Poisson Processes --
g 5.4.1.
t Shot Noise --
g 5.4.2.
t Sum Quota Sampling --
g 5.5.
t Spatial Poisson Processes --
g 5.6.
t Compound and Marked Poisson Processes --
g 5.6.1.
t Compound Poisson Processes --
g 5.6.2.
t Marked Poisson Processes --
g 6.
t Continuous Time Markov Chains --
g 6.1.
t Pure Birth Processes --
g 6.1.1.
t Postulates for the Poisson Process --
g 6.1.2.
t Pure Birth Process --
g 6.1.3.
t Yule Process --
g 6.2.
t Pure Death Processes --
g 6.2.1.
t Linear Death Process --
g 6.2.2.
t Cable Failure Under Static Fatigue --
g 6.3.
t Birth and Death Processes --
g 6.3.1.
t Postulates --
g 6.3.2.
t Sojourn Times --
g 6.3.3.
t Differential Equations of Birth and Death Processes --
g 6.4.
t Limiting Behavior of Birth and Death Processes --
g 6.5.
t Birth and Death Processes with Absorbing States --
g 6.5.1.
t Probability of Absorption into State 0 --
g 6.5.2.
t Mean Time Until Absorption --
g 6.6.
t Finite-State Continuous Time Markov Chains --
g 6.7.
t Poisson Process with a Markov Intensity --
g 7.
t Renewal Phenomena --
g 7.1.
t Definition of a Renewal Process and Related Concepts --
g 7.2.
t Some Examples of Renewal Processes --
g 7.2.1.
t Brief Sketches of Renewal Situations --
g 7.2.2.
t Block Replacement --
g 7.3.
t Poisson Process Viewed as a Renewal Process --
g 7.4.
t Asymptotic Behavior of Renewal Processes --
g 7.4.1.
t Elementary Renewal Theorem --
g 7.4.2.
t Renewal Theorem for Continuous Lifetimes --
g 7.4.3.
t Asymptotic Distribution of N(t) --
g 7.4.4.
t Limiting Distribution of Age and Excess Life --
g 7.5.
t Generalizations and Variations on Renewal Processes --
g 7.5.1.
t Delayed Renewal Processes --
g 7.5.2.
t Stationary Renewal Processes --
g 7.5.3.
t Cumulative and Related Processes --
g 7.6.
t Discrete Renewal Theory --
g 7.6.1.
t Discrete Renewal Theorem --
g 7.6.2.
t Deterministic Population Growth with Age Distribution --
g 8.
t Brownian Motion and Related Processes --
g 8.1.
t Brownian Motion and Gaussian Processes --
g 8.1.1.
t Little History --
g 8.1.2.
t Brownian Motion Stochastic Process --
g 8.1.3.
t Central Limit Theorem and the Invariance Principle --
g 8.1.4.
t Gaussian Processes --
g 8.2.
t Maximum Variable and the Reflection Principle --
g 8.2.1.
t Reflection Principle --
g 8.2.2.
t Time to First Reach a Level --
g 8.2.3.
t Zeros of Brownian Motion --
g 8.3.
t Variations and Extensions --
g 8.3.1.
t Reflected Brownian Motion --
g 8.3.2.
t Absorbed Brownian Motion --
g 8.3.3.
t Brownian Bridge --
g 8.3.4.
t Brownian Meander --
g 8.4.
t Brownian Motion with Drift --
g 8.4.1.
t Gambler's Ruin Problem --
g 8.4.2.
t Geometric Brownian Motion --
g 8.5.
t Ornstein---Uhlenbeck Process --
g 8.5.1.
t Second Approach to Physical Brownian Motion --
g 8.5.2.
t Position Process --
g 8.5.3.
t Long Run Behavior --
g 8.5.4.
t Brownian Measure and Integration --
g 9.
t Queueing Systems --
g 9.1.
t Queueing Processes --
g 9.1.1.
t Queueing Formula L=λW --
g 9.1.2.
t Sampling of Queueing Models --
g 9.2.
t Poisson Arrivals, Exponential Service Times --
g 9.2.1.
t M/M/1 System --
g 9.2.2.
t M/M/[∞] System --
g 9.2.3.
t M/M/s System --
g 9.3.
t General Service Time Distributions --
g 9.3.1.
t M/G/1 System --
g 9.3.2.
t M/G/[∞] System --
g 9.4.
t Variations and Extensions --
g 9.4.1.
t Systems with Balking --
g 9.4.2.
t Variable Service Rates --
g 9.4.3.
t System with Feedback --
g 9.4.4.
t Two-Server Overflow Queue --
g 9.4.5.
t Preemptive Priority Queues --
g 9.5.
t Open Acyclic Queueing Networks --
g 9.5.1.
t Basic Theorem --
g 9.5.2.
t Two Queues in Tandem --
g 9.5.3.
t Open Acyclic Networks --
g 9.5.4.
t Appendix: Time Reversibility --
g 9.5.5.
t Proof of Theorem 9.1 --
g 9.6.
t General Open Networks --
g 9.6.1.
t General Open Network --
g 10.
t Random Evolutions --
g 10.1.
t Two-State Velocity Model --
g 10.1.1.
t Two-State Random Evolution --
g 10.1.2.
t Telegraph Equation --
g 10.1.3.
t Distribution Functions and Densities in the Two-State Model --
g 10.1.4.
t Passage Time Distributions --
g 10.2.
t N-State Random Evolution --
g 10.2.1.
t Finite Markov Chains and Random Velocity Models --
g 10.2.2.
t Constructive Approach of Random Velocity Models --
g 10.2.3.
t Random Evolution Processes --
g 10.2.4.
t Existence-Uniqueness of the First-Order System (10.26) --
g 10.2.5.
t Single Hyperbolic Equation --
g 10.2.6.
t Spectral Properties of the Transition Matrix --
g 10.2.7.
t Recurrence Properties of Random Evolution --
g 10.3.
t Weak Law and Central Limit Theorem --
g 10.4.
t Isotropic Transport in Higher Dimensions --
g 10.4.1.
t Rayleigh Problem of Random Flights --
g 10.4.2.
t Three-Dimensional Rayleigh Model --
g 11.
t Characteristic Functions and Their Applications --
g 11.1.
t Definition of the Characteristic Function --
g 11.1.1.
t Two Basic Properties of the Characteristic Function --
g 11.2.
t Inversion Formulas for Characteristic Functions --
g 11.2.1.
t Fourier Reciprocity/Local Non-Uniqueness --
g 11.2.2.
t Fourier Inversion and Parseval's Identity --
g 11.3.
t Inversion Formula for General Random Variables --
g 11.4.
t Continuity Theorem --
g 11.4.1.
t Proof of the Continuity Theorem --
g 11.5.
t Proof of the Central Limit Theorem --
g 11.6.
t Stirling's Formula and Applications --
g 11.6.1.
t Poisson Representation of n! --
g 11.6.2.
t Proof of Stirling's Formula --
g 11.7.
t Local deMoivre---Laplace Theorem.
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