LEADER 01166nas 22003973a 450 001 9910892964303321 005 20240413021448.0 035 $a(CKB)958480261768 035 $a(CONSER)sn-82006456- 035 $a(DE-599)ZDB2776011-X 035 $a(EXLCZ)99958480261768 100 $a19820331b1949197u --- b 101 0 $aepo 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aScienca revuo 210 $aBeograd $cInternacia Scienca Asocia Esperantista$d1949- 215 $a1 online resource 311 08$aPrint version: Scienca revuo. 0048-9557 (DLC)sn 82006456 (OCoLC)8294622 531 0 $aSci. rev. 606 $aEsperanto$vPeriodicals 606 $aScience$vPeriodicals 606 $aEsperanto$2fast$3(OCoLC)fst00915363 606 $aScience$2fast$3(OCoLC)fst01108176 608 $aPeriodicals.$2fast 615 0$aEsperanto 615 0$aScience 615 7$aEsperanto. 615 7$aScience. 712 02$aInternacia Scienca Asocio Esperantista. 906 $aJOURNAL 912 $a9910892964303321 920 $aexl_impl conversion 996 $aScienca revuo$94272233 997 $aUNINA LEADER 05326nam 2200661 a 450 001 9910971661203321 005 20200520144314.0 010 $a9786613173836 010 $a9781283173834 010 $a1283173832 010 $a9780080930619 010 $a0080930611 035 $a(CKB)2670000000074970 035 $a(EBL)680811 035 $a(OCoLC)727648959 035 $a(SSID)ssj0000491979 035 $a(PQKBManifestationID)12214856 035 $a(PQKBTitleCode)TC0000491979 035 $a(PQKBWorkID)10477076 035 $a(PQKB)10527064 035 $a(MiAaPQ)EBC680811 035 $a(PPN)170600521 035 $a(FR-PaCSA)88811717 035 $a(FRCYB88811717)88811717 035 $a(EXLCZ)992670000000074970 100 $a20101228d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aExploring Monte Carlo methods /$fWilliam L. Dunn, J. Kenneth Shultis 205 $a1st ed. 210 $aAmsterdam ;$aBoston $cElsevier$dc2012 215 $a1 online resource (401 p.) 300 $aDescription based upon print version of record. 311 08$a9780444515759 311 08$a0444515755 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Exploring Monte Carlo Methods; Copyright; Dedication; Table of Contents; Preface; Chapter 1. Introduction; 1.1 What Is Monte Carlo?; 1.2 A Brief History of Monte Carlo; 1.3 Monte Carlo as Quadrature; 1.4 Monte Carlo as Simulation; 1.5 Preview of Things to Come; 1.6 Summary; Bibliography; Problems; Chapter 2. The Basis of Monte Carlo; 2.1 Single Continuous Random Variables; 2.2 Discrete Random Variables; 2.3 Multiple Random Variables; 2.4 The Law of Large Numbers; 2.5 The Central Limit Theorem; 2.6 Monte Carlo Quadrature; 2.7 Monte Carlo Simulation; 2.8 Summary; Bibliography 327 $aProblemsChapter 3. Pseudorandom Number Generators; 3.1 Linear Congruential Generators; 3.2 Structure of the Generated Random Numbers; 3.3 Characteristics of Good Random Number Generators; 3.4 Tests for Congruential Generators; 3.5 Practical Multiplicative Congruential Generators; 3.6 Shuffling a Generator's Output; 3.7 Skipping Ahead; 3.8 Combining Generators; 3.9 Other Random Number Generators; 3.10 Summary; Bibliography; Problems; Chapter 4. Sampling, Scoring, and Precision; 4.1 Sampling; 4.2 Scoring; 4.3 Accuracy and Precision; 4.4 Summary; Bibliography; Problems 327 $aChapter 5. Variance Reduction Techniques5.1 Use of Transformations; 5.2 Importance Sampling; 5.3 Systematic Sampling; 5.4 Stratified Sampling; 5.5 Correlated Sampling; 5.6 Partition of the Integration Volume; 5.7 Reduction of Dimensionality; 5.8 Russian Roulette and Splitting; 5.9 Combinations of Different Variance Reduction Techniques; 5.10 Biased Estimators; 5.11 Improved Monte Carlo Integration Schemes; 5.12 Summary; Bibliography; Problems; Chapter 6. Markov Chain Monte Carlo; 6.1 Markov Chains to the Rescue; 6.2 Brief Review of Probability Concepts; 6.3 Bayes Theorem 327 $a6.4 Inference and Decision Applications6.5 Summary; Bibliography; Problems; Chapter 7. Inverse Monte Carlo; 7.1 Formulation of the Inverse Problem; 7.2 Inverse Monte Carlo by Iteration; 7.3 Symbolic Monte Carlo; 7.4 Inverse Monte Carlo by Simulation; 7.5 General Applications of IMC; 7.6 Summary; Bibliography; Problems; Chapter 8. Linear Operator Equations; 8.1 Linear Algebraic Equations; 8.2 Linear Integral Equations; 8.3 Linear Differential Equations; 8.4 Eigenvalue Problems; 8.5 Summary; Bibliography; Problems; Chapter 9. The Fundamentals of Neutral Particle Transport 327 $a9.1 Description of the Radiation Field9.2 Radiation Interactions with the Medium; 9.3 Transport Equation; 9.4 Adjoint Transport Equation; 9.5 Summary; Bibliography; Problems; Chapter 10. Monte Carlo Simulation of Neutral Particle Transport; 10.1 Basic Approach for Monte Carlo Transport Simulations; 10.2 Geometry; 10.3 Sources; 10.4 Path-Length Estimation; 10.5 Purely Absorbing Media; 10.6 Type of Collision; 10.7 Time Dependence; 10.8 Particle Weights; 10.9 Scoring and Tallies; 10.10 An Example of One-Speed Particle Transport; 10.11 Monte Carlo Based on the Integral Transport Equation 327 $a10.12 Variance Reduction and Nonanalog Methods 330 $aExploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as ""Monte Carlo."" The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous ""Buffon's needle p 606 $aMonte Carlo method 615 0$aMonte Carlo method. 676 $a518/.282 700 $aDunn$b William L$g(William Lee),$f1944-$01796893 701 $aShultis$b J. Kenneth$0627176 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910971661203321 996 $aExploring Monte Carlo methods$94338896 997 $aUNINA