硬化
发表于 2025-3-25 06:14:33
Universitexthttp://image.papertrans.cn/n/image/669157.jpg
Trigger-Point
发表于 2025-3-25 11:23:52
https://doi.org/10.1007/978-3-319-90276-0Monte Carlo method; variance reduction; Quasi-Monte Carlo method; stochastic differential equation disc
尾随
发表于 2025-3-25 12:11:30
ologie gestattet es, zahlreiche und auf den ersten Blick sehr unterschiedliche Probleme bündig und einheitlich zu formulieren und sie einer gemeinsamen anschaulichen Vorstellung zu unterwerfen. Zur anschließenden . dieser Probleme trägt die Mengentheoretische Topologie im engeren Sinne ziemlich weni
手段
发表于 2025-3-25 16:51:18
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.
流逝
发表于 2025-3-25 23:05:15
The Monte Carlo Method and Applications to Option Pricing, Law of Large Numbers (without proof) and the different ways to measure its rate of convergence (quadratic mean, Central Limit theorem, Law of the Iterated Logarithm), we introduce the notion of confidence interval at a given confidence level, illustrated by a simple application to the pricing of a
Inflammation
发表于 2025-3-26 00:22:33
Variance Reduction, by replacing the random variable of interest by another one with the same expectation but lower variance. This chapter presents the main methods to do so: static and dynamic (regression) control variate, convexity methods (Jensen’s inequality), antithetic method, pre-conditioning (Blackwell-Rao), s
植物群
发表于 2025-3-26 07:55:46
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.
monologue
发表于 2025-3-26 12:09:07
http://reply.papertrans.cn/67/6692/669157/669157_28.png
degradation
发表于 2025-3-26 14:50:31
Stochastic Approximation with Applications to Finance,ep Learning applications. We show when and how to design a stochastic gradient or a zero search recursive stochastic algorithm. We prove the main convergence theorems (.... and in quadratic mean) as well as their rates of convergence (Central Limit theorem). The Ruppert & Polyak averaging procedure,
single
发表于 2025-3-26 20:31:42
Discretization Scheme(s) of a Brownian Diffusion,the (discrete time and continuous) Euler scheme and the Milstein scheme. The existence of moments, the strong (or pathwise) convergence rate in . (and a:s:) of both schemes are established under Lipschitz assumptions of the diffusion coeffcients (Euler scheme) or of their partial derivatives (Milste