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Monte Carlo and Quasi-Monte Carlo Methods

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Cover of 'Monte Carlo and Quasi-Monte Carlo Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Multilevel Monte Carlo Implementation for SDEs Driven by Truncated Stable Processes
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    Chapter 2 Construction of a Mean Square Error Adaptive Euler–Maruyama Method With Applications in Multilevel Monte Carlo
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    Chapter 3 Vandermonde Nets and Vandermonde Sequences
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    Chapter 4 Path Space Markov Chain Monte Carlo Methods in Computer Graphics
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    Chapter 5 Walsh Figure of Merit for Digital Nets: An Easy Measure for Higher Order Convergent QMC
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    Chapter 6 Some Results on the Complexity of Numerical Integration
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    Chapter 7 Approximate Bayesian Computation: A Survey on Recent Results
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    Chapter 8 Multilevel Monte Carlo Simulation of Statistical Solutions to the Navier–Stokes Equations
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    Chapter 9 Unbiased Simulation of Distributions with Explicitly Known Integral Transforms
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    Chapter 10 Central Limit Theorem for Adaptive Multilevel Splitting Estimators in an Idealized Setting
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    Chapter 11 Comparison Between LS -Sequences and $$\beta $$ β -Adic van der Corput Sequences
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    Chapter 12 Computational Higher Order Quasi-Monte Carlo Integration
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    Chapter 13 Numerical Computation of Multivariate Normal Probabilities Using Bivariate Conditioning
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    Chapter 14 Non-nested Adaptive Timesteps in Multilevel Monte Carlo Computations
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    Chapter 15 On ANOVA Decompositions of Kernels and Gaussian Random Field Paths
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    Chapter 16 The Mean Square Quasi-Monte Carlo Error for Digitally Shifted Digital Nets
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    Chapter 17 Uncertainty and Robustness in Weather Derivative Models
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    Chapter 18 Reliable Adaptive Cubature Using Digital Sequences
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    Chapter 19 Optimal Point Sets for Quasi-Monte Carlo Integration of Bivariate Periodic Functions with Bounded Mixed Derivatives
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    Chapter 20 Adaptive Multidimensional Integration Based on Rank-1 Lattices
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    Chapter 21 Path Space Filtering
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    Chapter 22 Tractability of Multivariate Integration in Hybrid Function Spaces
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    Chapter 23 Derivative-based global sensitivity measures and their link with Sobol sensitivity indices
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    Chapter 24 Bernstein Numbers and Lower Bounds for the Monte Carlo Error
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    Chapter 25 A Note on the Importance of Weak Convergence Rates for SPDE Approximations in Multilevel Monte Carlo Schemes
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    Chapter 26 A Strategy for Parallel Implementations of Stochastic Lagrangian Simulation
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    Chapter 27 A New Rejection Sampling Method for Truncated Multivariate Gaussian Random Variables Restricted to Convex Sets
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    Chapter 28 Van der Corput and Golden Ratio Sequences Along the Hilbert Space-Filling Curve
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    Chapter 29 Uniform Weak Tractability of Weighted Integration
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    Chapter 30 Incremental Greedy Algorithm and Its Applications in Numerical Integration
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    Chapter 31 On “Upper Error Bounds for Quadrature Formulas on Function Classes” by K.K. Frolov
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    Chapter 32 Tractability of Function Approximation with Product Kernels
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    Chapter 33 Discrepancy Estimates For Acceptance-Rejection Samplers Using Stratified Inputs
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Title
Monte Carlo and Quasi-Monte Carlo Methods
Published by
Springer International Publishing, June 2016
DOI 10.1007/978-3-319-33507-0
ISBNs
978-3-31-933505-6, 978-3-31-933507-0
Authors

Goda, Takashi, Ohori, Ryuichi, Suzuki, Kosuke, Yoshiki, Takehito

Editors

Ronald Cools, Dirk Nuyens

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 25%
Unknown 3 75%
Readers by discipline Count As %
Physics and Astronomy 1 25%
Unknown 3 75%