Josef Dick, Frances Y. Kuo, Gareth W. Peters, Ian H. Sloan's Monte Carlo and Quasi-Monte Carlo Methods 2012 PDF

By Josef Dick, Frances Y. Kuo, Gareth W. Peters, Ian H. Sloan

ISBN-10: 3642410952

ISBN-13: 9783642410956

This publication represents the refereed court cases of the 10th overseas convention on Monte Carlo and Quasi-Monte Carlo tools in medical Computing that used to be held on the college of latest South Wales (Australia) in February 2012. those biennial meetings are significant occasions for Monte Carlo and the most suitable occasion for quasi-Monte Carlo examine. The court cases contain articles in response to invited lectures in addition to conscientiously chosen contributed papers on all theoretical points and functions of Monte Carlo and quasi-Monte Carlo tools. The reader might be supplied with details on most up-to-date advancements in those very energetic components. The ebook is a superb reference for theoreticians and practitioners drawn to fixing high-dimensional computational difficulties bobbing up, specifically, in finance, statistics and special effects.

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Cambridge University Press, Cambridge (2002) An Introduction to Stochastic Particle Integration Methods: With Applications to Risk and Insurance Pierre Del Moral, Gareth W. Peters, and Christelle Vergé Abstract This article presents a guided introduction to a general class of interacting particle methods and explains throughout how such methods may be adapted to solve general classes of inference problems encountered in actuarial science and risk management. Along the way, the resulting specialized Monte Carlo solutions are discussed in the context of how they complemented alternative approaches adopted in risk management, including closed form bounds and asymptotic results for functionals of tails of risk processes.

J. Differ. Equ. 207, 285–302 (2004) 22. : Affine processes on positive semidefinite matrices. Ann. Appl. Probab. 21, 397–463 (2011) 23. : Estimationg the Wishart affine stochastic correlation model using the empirical characteristic function. Working paper, University Padova (2008) 24. : Hedging (co)variance risk with variance swaps. Int. J. Theor. Appl. Finance 14, 899, (2011) 25. : Option pricing when correlations are stochastic: an analytical framework. Review of Derivatives Research 10, 151–180 (2007) 26.

3 The Small Ball Inequality Lower bounds on the discrepancy function are related through proof techniques to subjects in different areas of mathematics. They include, in particular, the so-called small deviation inequalities for the Brownian sheet in probability theory, complexity bounds for certain Sobolev spaces in approximation theory, and a combinatorial inequality involving multivariate Haar functions in the unit cube. We refer the reader to the references [3–5, 8] for more information, and emphasize that the questions in probability and approximation theory are parts of very broad areas of investigation with additional points of contact with discrepancy theory and many variations of the underlying themes.

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Monte Carlo and Quasi-Monte Carlo Methods 2012 by Josef Dick, Frances Y. Kuo, Gareth W. Peters, Ian H. Sloan


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