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Titlebook: Numerical Probability; An Introduction with Gilles Pagès Textbook 2018 Springer Nature Switzerland AG 2018 Monte Carlo method.variance redu

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11#
發(fā)表于 2025-3-23 13:46:46 | 只看該作者
12#
發(fā)表于 2025-3-23 14:10:28 | 只看該作者
13#
發(fā)表于 2025-3-23 20:32:34 | 只看該作者
Miscellany,cluded the proofs of two specific mathematical results (discrepancy of the Halton sequence and Pitman-Yor identity) which are not essential in the context of numerical applications but give the mathematical flavor of the underlying theories we use at several places in the book.
14#
發(fā)表于 2025-3-24 01:00:47 | 只看該作者
0172-5939 an extensive bibliography.This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance...Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation,
15#
發(fā)表于 2025-3-24 03:18:00 | 只看該作者
Textbook 2018lude the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well
16#
發(fā)表于 2025-3-24 07:41:04 | 只看該作者
Simulation of Random Variables,of pseudorandom numbers, the inverse distribution function method and von Neumann’s acceptance-rejection method, with applications to the simulation of Gaussian vectors, (fractional) Brownian motion and Poisson process paths.
17#
發(fā)表于 2025-3-24 13:09:33 | 只看該作者
The Quasi-Monte Carlo Method,-random numbers are replaced by deterministic computable sequences of .-valued vectors which, once substituted . in place of pseudo-random numbers in the Monte Carlo method, may significantly speed up its rate of convergence, making it . independent of the structural dimension . of the simulation.
18#
發(fā)表于 2025-3-24 18:33:56 | 只看該作者
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發(fā)表于 2025-3-24 19:31:49 | 只看該作者
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發(fā)表于 2025-3-24 23:29:07 | 只看該作者
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