Exploring Monte Carlo Methods
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Exploring Monte Carlo Methods
Shultis, J. Kenneth; Dunn, William L.
Elsevier Science & Technology
06/2011
398
Dura
Inglês
9780444515759
15 a 20 dias
660
Descrição não disponível.
1 Introduction
2 The Basis of Monte Carlo
3 Pseudorandom Number Generators
4 Sampling, Scoring, and Precision
5 Variance Reduction Techniques
6 Markov Chain Monte Carlo
7 Inverse Monte Carlo
8 Linear Operator Equations
9 The Fundamentals of Neutral Particle Transport
10 Monte Carlo Simulation of Neutral Particle Transport
Appendices
2 The Basis of Monte Carlo
3 Pseudorandom Number Generators
4 Sampling, Scoring, and Precision
5 Variance Reduction Techniques
6 Markov Chain Monte Carlo
7 Inverse Monte Carlo
8 Linear Operator Equations
9 The Fundamentals of Neutral Particle Transport
10 Monte Carlo Simulation of Neutral Particle Transport
Appendices
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
adjoint transport equation; antithetic variates; Bayesian analysis; biased estimators; biased sampling; Boltzmann transport equation; CDF; central limit theorem; coding; COG; combinatorial geometry; combining variance reduction methods; conditional distributions; confidence intervals; correlated sampling; cross sections; discrete random variables; EGSnrc; exponential attenuation; flux and fluence; Fredholm integral equations; GEANT4; Gibbs sampling; Helmholtz equation; IMC by iteration; IMC simulations; importance sampling; inference and decision making; inverse Monte Carlo (IMC); inverse problems; ITS; joint distributions; Laplace equation; law of large numbers; linear algebraic equation; linear differential equations; marginal distributions; Markov chain; Markov chain Monte Carlo (MCMC); MC for integral transport equation; MC for linear operators; MCNP5/MCNPX; Metropolis-Hastings algorithm; minimal pseudorandom number generator; moment generating functions (MGF); Monte Carlo (MC); neutral particle transport; neutral particles; particle tallies; particle tracking; PDF; PDF/CDF figures; PENELOPE; Poisson equation; properties of various PDFs; quasirandom numbers; reaction rate density; Russian roulette and splitting; sample/population means and variances; sampling distributions; SCALE; SRIM; standard deviation; stratified sampling; strong form; sums of random variables; symbolic IMC (SMC); systematic sampling; transition matrices and kernels; transport; transport codes summaries; transport simulation; TRIPOLI; uncertainties in IMC; variance reduction; walking on spheres; weak form
1 Introduction
2 The Basis of Monte Carlo
3 Pseudorandom Number Generators
4 Sampling, Scoring, and Precision
5 Variance Reduction Techniques
6 Markov Chain Monte Carlo
7 Inverse Monte Carlo
8 Linear Operator Equations
9 The Fundamentals of Neutral Particle Transport
10 Monte Carlo Simulation of Neutral Particle Transport
Appendices
2 The Basis of Monte Carlo
3 Pseudorandom Number Generators
4 Sampling, Scoring, and Precision
5 Variance Reduction Techniques
6 Markov Chain Monte Carlo
7 Inverse Monte Carlo
8 Linear Operator Equations
9 The Fundamentals of Neutral Particle Transport
10 Monte Carlo Simulation of Neutral Particle Transport
Appendices
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
adjoint transport equation; antithetic variates; Bayesian analysis; biased estimators; biased sampling; Boltzmann transport equation; CDF; central limit theorem; coding; COG; combinatorial geometry; combining variance reduction methods; conditional distributions; confidence intervals; correlated sampling; cross sections; discrete random variables; EGSnrc; exponential attenuation; flux and fluence; Fredholm integral equations; GEANT4; Gibbs sampling; Helmholtz equation; IMC by iteration; IMC simulations; importance sampling; inference and decision making; inverse Monte Carlo (IMC); inverse problems; ITS; joint distributions; Laplace equation; law of large numbers; linear algebraic equation; linear differential equations; marginal distributions; Markov chain; Markov chain Monte Carlo (MCMC); MC for integral transport equation; MC for linear operators; MCNP5/MCNPX; Metropolis-Hastings algorithm; minimal pseudorandom number generator; moment generating functions (MGF); Monte Carlo (MC); neutral particle transport; neutral particles; particle tallies; particle tracking; PDF; PDF/CDF figures; PENELOPE; Poisson equation; properties of various PDFs; quasirandom numbers; reaction rate density; Russian roulette and splitting; sample/population means and variances; sampling distributions; SCALE; SRIM; standard deviation; stratified sampling; strong form; sums of random variables; symbolic IMC (SMC); systematic sampling; transition matrices and kernels; transport; transport codes summaries; transport simulation; TRIPOLI; uncertainties in IMC; variance reduction; walking on spheres; weak form
