Simulation and Monte Carlo

DOI10.1002/9780470061336zbMath1117.65006OpenAlexW2480977715MaRDI QIDQ3415184

J. S. Dagpunar

Publication date: 15 January 2007

Published in: Wiley Series in Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/9780470061336

zbMATH Keywords

textbookMarkov chain Monte CarloMonte Carlo methodsMarkov chainsimulationsvariance reductionpseudo-random numbersrandom number generationmethodstandard distributionsuniform random numberssimulation and finance

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Numerical methods (including Monte Carlo methods) (91G60) Discrete-time Markov processes on general state spaces (60J05) Probability distributions: general theory (60E05) Queueing theory (aspects of probability theory) (60K25) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Characterization and structure theory of statistical distributions (62E10) Research exposition (monographs, survey articles) pertaining to numerical analysis (65-02) Analysis of variance and covariance (ANOVA) (62J10) General theory of distribution modulo (1) (11K06) Pseudo-random numbers; Monte Carlo methods (11K45) Probabilistic methods, stochastic differential equations (65Cxx)

Related Items (11)

Bayesian estimation under a mixture of the Burr type XII distribution and its reciprocal ⋮ On the computation of the survival probability of Brownian motion with drift in a closed time interval when the absorbing boundary is a step function ⋮ Progressively Type-II censored competing risks data for exponential distributions based on sequential order statistics ⋮ Bayesian estimation of generalized hyperbolic skewed student GARCH models ⋮ Generating generalized inverse Gaussian random variates ⋮ A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain ⋮ Stochastic Filtering Methods in Electronic Trading ⋮ Bayesian quantile regression for ordinal models ⋮ A general method of computing mixed Poisson probabilities by Monte Carlo sampling ⋮ Discretization-based direct random sample generation ⋮ Universal methods for generating random variables with a given characteristic function

Uses Software

• Maple
• AS 183

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