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Table of Contents
Intro; Preface; Contents; Contributors; Part I Invited Papers; 1 Design and Analysis of Simulation Experiments; 1.1 Introduction; 1.2 Basic Linear Regression and Designs; 1.3 Assumptions Versus Practice; 1.4 Factor Screening: Sequential Bifurcation; 1.5 Kriging Metamodels and Their Designs; 1.6 Simulation Optimization; References; 2 A Review of Simulation Usage in the New Zealand Electricity Market; 2.1 Introduction to Wholesale Electricity Markets; 2.1.1 Pricing of Electricity; 2.2 The New Zealand Electricity Market; 2.2.1 The Need for Simulation: Pricing in the NZEM
2.3 Optimal Offers for Generation2.3.1 A Simplified Problem; 2.3.2 Using Simulation for the General Problem; 2.4 Bid Optimization for Large Consumers of Electricity; 2.4.1 Reserve Co-optimization; 2.4.2 Optimization of Consumption and Reserves; 2.5 Conclusions; References; 3 Power and Sample Size Considerations in Psychometrics; 3.1 Introduction; 3.2 Power and Sample Size in a Conditional Maximum Likelihood Framework; 3.3 Power of Pseudo-Exact or Conditional Tests of Assumptions of the Rasch Model; 3.4 Linear Models and Least Squares Approach; 3.5 Numerical Examples and Comparisons
3.6 DiscussionReferences; 4 Bootstrap Change Point Testing for Dependent Data; 4.1 Introduction; 4.2 Procedures with Weakly Dependent Regressors and Errors; 4.3 Dependent Wild Bootstrap; 4.4 Simulations; References; Part II Simulation for Mathematical Modeling and Analysis; 5 The Covariation Matrix of Solution of a Linear Algebraic System by the Monte Carlo Method; 5.1 Introduction; 5.2 The Monte Carlo Method of Solution; 5.3 Sufficient Conditions for the Convergence of the Series tildeH; 5.4 The Covariation Matrix R of the Vector; 5.5 Estimate of the Number of Iterations M
5.6 Numerical Examples5.7 Conclusions; References; 6 Large-Scale Simulation of Acoustic Waves in Random Multiscale Media; 6.1 Introduction; 6.2 The Model and Governing Equation; 6.3 Subgrid Modeling; 6.3.1 The Anisotropic Case; 6.4 Numerical Verification of the Above Obtained Formulas; 6.5 Conclusion; References; 7 Parameter Inference for Stochastic Differential Equations with Density Tracking by Quadrature; 7.1 Introduction; 7.2 Methods; 7.3 Results; 7.4 Discussion and Conclusion; References; 8 New Monte Carlo Algorithm for Evaluation of Outgoing Polarized Radiation; 8.1 Introduction
8.2 Mathematical Model of Polarized Light Propagation and the Problem Statement8.3 A Modification of N. N. Chentsov Method for an Unknown Probability Density Evaluation in Application to the Problem of Evaluation of an Angular Distribution of the Radiation Scattered by Media; 8.4 Numerical Results and Discussion; 8.5 Conclusion; References; Part III Simulation for Stochastic Processes and Their Applications; 9 Simulation of Stochastic Processes with Generation and Transport of Particles; 9.1 Introduction; 9.2 Evolution of Branching Random Walks; 9.3 Simulation of Branching Random Walks
2.3 Optimal Offers for Generation2.3.1 A Simplified Problem; 2.3.2 Using Simulation for the General Problem; 2.4 Bid Optimization for Large Consumers of Electricity; 2.4.1 Reserve Co-optimization; 2.4.2 Optimization of Consumption and Reserves; 2.5 Conclusions; References; 3 Power and Sample Size Considerations in Psychometrics; 3.1 Introduction; 3.2 Power and Sample Size in a Conditional Maximum Likelihood Framework; 3.3 Power of Pseudo-Exact or Conditional Tests of Assumptions of the Rasch Model; 3.4 Linear Models and Least Squares Approach; 3.5 Numerical Examples and Comparisons
3.6 DiscussionReferences; 4 Bootstrap Change Point Testing for Dependent Data; 4.1 Introduction; 4.2 Procedures with Weakly Dependent Regressors and Errors; 4.3 Dependent Wild Bootstrap; 4.4 Simulations; References; Part II Simulation for Mathematical Modeling and Analysis; 5 The Covariation Matrix of Solution of a Linear Algebraic System by the Monte Carlo Method; 5.1 Introduction; 5.2 The Monte Carlo Method of Solution; 5.3 Sufficient Conditions for the Convergence of the Series tildeH; 5.4 The Covariation Matrix R of the Vector; 5.5 Estimate of the Number of Iterations M
5.6 Numerical Examples5.7 Conclusions; References; 6 Large-Scale Simulation of Acoustic Waves in Random Multiscale Media; 6.1 Introduction; 6.2 The Model and Governing Equation; 6.3 Subgrid Modeling; 6.3.1 The Anisotropic Case; 6.4 Numerical Verification of the Above Obtained Formulas; 6.5 Conclusion; References; 7 Parameter Inference for Stochastic Differential Equations with Density Tracking by Quadrature; 7.1 Introduction; 7.2 Methods; 7.3 Results; 7.4 Discussion and Conclusion; References; 8 New Monte Carlo Algorithm for Evaluation of Outgoing Polarized Radiation; 8.1 Introduction
8.2 Mathematical Model of Polarized Light Propagation and the Problem Statement8.3 A Modification of N. N. Chentsov Method for an Unknown Probability Density Evaluation in Application to the Problem of Evaluation of an Angular Distribution of the Radiation Scattered by Media; 8.4 Numerical Results and Discussion; 8.5 Conclusion; References; Part III Simulation for Stochastic Processes and Their Applications; 9 Simulation of Stochastic Processes with Generation and Transport of Particles; 9.1 Introduction; 9.2 Evolution of Branching Random Walks; 9.3 Simulation of Branching Random Walks