Tabla de Contenidos: “…Decision Analysis. -- 16. Monte Carlo Simulation. -- 17. Optimization Simulation. -- Appendix. …”

Tabla de Contenidos: “…chapter 1 The Golem of Prague / chapter 2 Small Worlds and Large Worlds / chapter 3 Sampling the Imaginary / chapter 4 Linear Models / chapter 5 Multivariate Linear Models / chapter 6 Overfitting, Regularization, and Information Criteria / chapter 7 Interactions / chapter 8 Markov Chain Monte Carlo / chapter 9 Big Entropy and the Generalized Linear Model / chapter 10 Counting and Classification / chapter 11 Monsters and Mixtures / chapter 12 Multilevel Models / chapter 13 Adventures in Covariance / chapter 14 Missing Data and Other Opportunities / chapter 15 Horoscopes…”

Tabla de Contenidos: “…3.7 Choosing the Best Distribution and Assessing the Results3.8 Conclusions; Questions; Bibliography; 4 Monte Carlo Simulation; 4.1 Introduction; 4.2 Monte Carlo Simulation Basics; 4.3 Additional Statistical Distributions; 4.4 Sampling a Statistical Distribution; 4.5 Basic Steps for Performing a Monte Carlo Simulation; 4.6 Monte Carlo Method Summary; Questions; Bibliography; 5 Load-Strength Interference; 5.1 Introduction; 5.2 Distributed Load and Strength; 5.3 Analysis of Load-Strength Interference; 5.4 Effect of Safety Margin and Loading Roughness on Reliability (Multiple Load Applications)…”

Tabla de Contenidos: “…Front Cover; Dedication; Contents; Preface; Chapter 1 - Probability and counting; Chapter 2 - Conditional probability; Chapter 3 - Random variables and their distributions; Chapter 4 - Expectation; Chapter 5 - Continuous random variables; Chapter 6 - Moments; Chapter 7 - Joint distributions; Chapter 8 - Transformations; Chapter 9 - Conditional expectation; Chapter 10 - Inequalities and limit theorems; Chapter 11 - Markov chains; Chapter 12 - Markov chain Monte Carlo; Chapter 13 - Poisson processes; Appendix A - Math; Appendix B - R; Appendix C - Table of distributions; Bibliography…”

Tabla de Contenidos: “…Front cover; Contents; Preface; Chapter 1: Notation, definitions, and basic inference; Chapter 2: Traditional time domain models; Chapter 3: The frequency domain; Chapter 4: Dynamic linear models; Chapter 5: State-space TVAR models; Chapter 6: General state-space models andsequential Monte Carlo methods; Chapter 7: Mixture models in time series; Chapter 8: Topics and examples in multipletime series; Chapter 9: Vector AR and ARMA models; Chapter 10: Multivariate DLMs and covariance models; Bibliography; Author Index; Subject Index; Back cover…”

Tabla de Contenidos: “…Chapter 1: Options Concepts -- Chapter 2: Financial Derivatives -- Chapter 3: Basic Algorithms -- Chapter 4: Object-Oriented Techniques -- Chapter 5: Design Patterns for Options Processing -- Chapter 6: Template-Based Techniques -- Chapter 7: STL for Derivatives Programming -- Chapter 8: Functional Programming Techniques -- Chapter 9: Linear Algebra Algorithms -- Chapter 10: Algorithms for Numerical Analysis -- Chapter 11: Models Based on Differential Equations -- Chapter 12: Basic Models for Option Pricing -- Chapter 13: Monte-Carlo Methods -- Chapter 14: Using C++ Libraries for Finance.…”

Tabla de Contenidos: “…Front Cover; Foreword; Table of Contents; Preface; Preface to the Second Edition; Chapter 1: Introduction; Chapter 2: The Physics of Light Transport; Chapter 3: Monte Carlo Methods; Chapter 4: Strategies for Computing Light Transport; Chapter 5: Stochastic Path-Tracing Algorithms; Chapter 6: Stochastic Radiosity; Chapter 7: Hybrid Algorithms; Chapter 8: The Quest for Ultimate Realism and Speed; Chapter 9: Conclusion; Appendix A: A Class Library for Global Illumination; Appendix B: Hemispherical Coordinates; Appendix C: Theoretical Analysis of Stochastic Relaxation Radiosity; Bibliography…”

Tabla de Contenidos: “…, 3.2 Monte Carlo Simulation and Correlation, 3.2.1 Independent Random Uncertain Events - How Real is That?…”

Tabla de Contenidos: “…Mixture models and clustering -- Non-finite mixture model -- Dirichlet process -- Continuous mixtures -- Some common distributions are mixtures -- Summary -- Exercises -- Chapter 8: Gaussian Processes -- Linear models and non-linear data -- Modeling functions -- Multivariate Gaussians and functions -- Covariance functions and kernels -- Gaussian processes -- Gaussian process regression -- Gaussian process regression with PyMC -- Setting priors for the length scale -- Gaussian process classification -- GPs for space flu -- Cox processes -- Coal mining disasters -- Red wood -- Regression with spatial autocorrelation -- Hilbert space GPs -- HSGP with Bambi -- Summary -- Exercises -- Chapter 9: Bayesian Additive Regression Trees -- Decision trees -- BART models -- Bartian penguins -- Partial dependence plots -- Individual conditional plots -- Variable selection with BART -- Distributional BART models -- Constant and linear response -- Choosing the number of trees -- Summary -- Exercises -- Chapter 10: Inference Engines -- Inference engines -- The grid method -- Quadratic method -- Markovian methods -- Monte Carlo -- Markov chain -- Metropolis-Hastings -- Hamiltonian Monte Carlo -- Sequential Monte Carlo -- Diagnosing the samples -- Convergence -- Trace plot -- Rank plot -- , (R hat) -- Effective Sample Size (ESS) -- Monte Carlo standard error -- Divergences -- Keep calm and keep trying -- Summary -- Exercises -- Chapter 11: Where to Go Next -- Other Books You May Enjoy -- Index…”

Tabla de Contenidos: “…Introduction and overview -- Statistical aspects of experimental design in experimental economics -- Treatment testing -- Theory testing, regression, and dependence -- Modelling of decision times using regression analysis -- Dealing with discreteness in experimental data -- Ordinal data in experimetrics -- Dealing with heterogeneity : finite mixture models -- Simulating experimental data, and the Monte Carlo method -- Introduction to the method of maximum simulated likelihood (MSL) -- Dealing with zeros : hurdle models -- Choice under risk : theoretical issues -- Choice under risk : econometric modelling -- Optimal design in binary choice experiments -- Social preference models -- Repeated games and quantal response models -- Depth of reasoning models -- Learning models -- Summary and conclusion…”

Tabla de Contenidos: “…Front Cover; Contents; List of Figures; List of Tables; Preface; Chapter 1: Introduction and Overview; Part I: Probability and Random Variables; Chapter 2: Probability; Chapter 3: Discrete Random Variables and Their Distributions; Chapter 4: Continuous Distributions; Chapter 5: Computer Simulations and Monte Carlo Methods; Part II: Stochastic Processes; Chapter 6: Stochastic Processes; Chapter 7: Queuing Systems; Part III: Statistics205; Chapter 8: Introduction to Statistics; Chapter 9: Statistical Inference I; Chapter 10: Statistical Inference II; Chapter 11: Regression; Part IV: Appendix…”

Tabla de Contenidos: “…Fundamentals of the q programming language -- Dictionaries and tables : the q fundamentals -- Functions -- Editors and other tools -- Debugging q code -- Splayed and partitioned tables -- Joins -- Parallelisation -- Data cleaning and filtering -- Parse trees -- A few use cases -- Basic overview of statistics -- Linear regression -- Time series econometrics -- Fourier transform -- Eigensystem and PCA -- Outlier detection -- Simulating asset prices -- Basic principles of machine learning -- Linear regression with regularisation -- Nearest neighbours -- Neural networks -- AdaBoost with stumps -- Trees -- Forests -- Unsupervised machine learning : the Apriori algorithm -- Processing information -- Towards AI : Monte Carlo tree search -- Econophysics : the agent-based computational models -- Epilogue: Art…”

Tabla de Contenidos: “…Equity Valuation; Contents; Foreword; Preface; Acknowledgments; Abbreviations; Part I Discounted Cash Flow (DCF) Models; Part II Monte Carlo Free Cash Flow to the Firm (MC-FCFF) Models (Deutsche Bank/DWS); Part III Beyond Earnings: A User's Guide to Excess Return Models and the HOLT CFROI® Framework; Part IV Morgan Stanley ModelWare's Approach to Intrinsic Value: Focusing on Risk-Reward Trade-offs; Part V UBS VCAM and EGQ Regression-based Valuation; Part VI Leverage Buyout (LBO) Models; Part VII Valuation 101: Approaches and Alternatives; Part VIII Final Thoughts on Valuation; Index…”

Tabla de Contenidos: “…Censored Data; Chapter 11. Monte Carlo Risk Assessment; Chapter 12. Final Remarks; Appendix 1: Some Basic Statistical Methods; Appendix 2: Statistical Tables…”

Tabla de Contenidos: “…10 Multivariate Volatility Models and Their Applications11 State-Space Models and Kalman Filter; 12 Markov Chain Monte Carlo Methods with Applications; Index…”

Tabla de Contenidos: “…; Calibration Exercise; Calibration Trick: Bet Money (or Even Just Pretend To); Further Improvements on Calibration; Conceptual Obstacles to Calibration; The Effects of Calibration Training; Notes; Chapter 6 Quantifying Risk through Modeling; How Not to Quantify Risk; Real Risk Analysis: The Monte Carlo; An Example of the Monte Carlo Method and Risk; Tools and Other Resources for Monte Carlo Simulations…”