Introduction to Robust and Quasi-Robust Statistical Methods, W.J.J. Rey

Автор: Huang, Kerson,
Название: Introduction to statistical physics
ISBN: 1420079026 ISBN-13(EAN): 9781420079029
Издательство: Taylor&Francis
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Цена: 71450.00 T
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Описание: Written by a world-renowned theoretical physicist, this textbook familiarizes advanced undergraduate students with the different aspects of statistical physics. Along with many exercises, it includes a discussion of phase transition in thermodynamics. It also covers stochastic processes.

Автор: Harald Niederreiter; Peter Hellekalek; Gerhard Lar
Название: Monte Carlo and Quasi-Monte Carlo Methods 1996
ISBN: 038798335X ISBN-13(EAN): 9780387983356
Издательство: Springer
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Цена: 88500.00 T
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Описание: Monte Carlo methods are numerical methods based on random sampling and quasi-Monte Carlo methods are their deterministic versions. These proceedings will be of interest to graduate students and researchers in Monte Carlo and quasi-Monte Carlo methods, to numerical analysts, and to practitioners of simulation methods.

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 184750.00 T
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Автор: Becketti
Название: Introduction to Time Series Using Stata
ISBN: 1597181323 ISBN-13(EAN): 9781597181327
Издательство: Taylor&Francis
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Цена: 75530.00 T
Наличие на складе: Невозможна поставка.
Описание: Recent decades have witnessed explosive growth in new and powerful tools for timeseries analysis. These innovations have overturned older approaches to forecasting, macroeconomic policy analysis, the study of productivity and long-run economic growth, and the trading of financial assets. Familiarity with these new tools on time series is an essential skill for statisticians, econometricians, and applied researchers. Introduction to Time Series Using Stata provides a step-by-step guide to essential timeseries techniques—from the incredibly simple to the quite complex—and, at the same time, demonstrates how these techniques can be applied in the Stata statistical package. The emphasis is on an understanding of the intuition underlying theoretical innovations and an ability to apply them. Real-world examples illustrate the application of each concept as it is introduced, and care is taken to highlight the pitfalls, as well as the power, of each new tool. Sean Becketti is a financial industry veteran with three decades of experience in academics, government, and private industry. Over the last two decades, Becketti has led proprietary research teams at several leading financial firms, responsible for the models underlying the valuation, hedging, and relative value analysis of some of the largest fixed-income portfolios in the world.

Автор: Gunther Leobacher; Friedrich Pillichshammer
Название: Introduction to Quasi-Monte Carlo Integration and Applications
ISBN: 3319034243 ISBN-13(EAN): 9783319034249
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book introduces the basic concepts of quasi-Monte Carlo methods for numerical integration and the theory behind them. It also presents methods currently used in research and discusses practical applications with an emphasis on finance-related problems.

Автор: Plichta
Название: Munros Statistical methods health care 6E
ISBN: 1451187947 ISBN-13(EAN): 9781451187946
Издательство: Lippincott Williams & Wilkins
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Цена: 90370.00 T
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Описание: This text provides students with a solid foundation for understanding data analysis and specific statistical techniques. Focusing on the most current and frequently used statistical methods in today's health care literature, the book covers essential material for a variety of program levels including in-depth courses beyond the basic statistics course. Well-organized, clear text discussions and great learning tools help students overcome the complexities and fully comprehend the concepts of this often intimidating area of study.

Автор: Josef Dick; Frances Y. Kuo; Gareth W. Peters; Ian
Название: Monte Carlo and Quasi-Monte Carlo Methods 2012
ISBN: 3662514389 ISBN-13(EAN): 9783662514382
Издательство: Springer
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Цена: 130430.00 T
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Описание: This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February 2012.

Автор: Kai-Tai Fang; Fred J. Hickernell; Harald Niederrei
Название: Monte Carlo and Quasi-Monte Carlo Methods 2000
ISBN: 354042718X ISBN-13(EAN): 9783540427186
Издательство: Springer
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Цена: 153720.00 T
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Описание: Contains the proceedings of the Fourth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing held in Hong Kong in 2000. It includes surveys of multidimensional numerical integration, low-discrepancy point sets, random number generation and applications.

Автор: Andreas Prohl
Название: Projection and Quasi-Compressibility Methods for Solving the Incompressible Navier-Stokes Equations
ISBN: 3519027232 ISBN-13(EAN): 9783519027232
Издательство: Springer
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Цена: 60940.00 T
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Описание: The numerical treatment of the evolutionary incompressible Navier-Stokes equations, which determine many practicaIly relevant fluid flows, is an area of considerable interest for industrial as weIl as scientific applications. Im- portant for drawing furt her conclusions for the behavior of certain flows in diverse disciplines such as (astro-)physics, engineering, meteorology, oceanog- raphy, or biology is a reliable, robust and efficient numerical model. The goal of computing highly complex flows requires the development of sophisticated algorithms. In general, numerical schemes which do not cause high computa- tional cost, often suffer from stability or reliability problems and vice versa. So, it demands a numerical and physical a-priori knowledge from the user in order to select the "best fitting algorithm" for a particular problem under consideration. The use of knowledge about physical phenomena appearing in a specific problem aIlows the relaxation of some robustness-conditions that otherwise need to be imposed on the numerical scheme in order to ensure reliability with respect to the convergence behavior. To this end, this leads to permittance of numerical models simulating continuous flows which do not satisfy severe stability restrictions that lead to robust schemes, with the advantage of lower computational costs necessary to obtain the same accu- racy. A major part of this book is devoted to such schemes that are of great importance: classical projection methods 01 high er order and nonstationary quasi-compressibility methods.

Автор: Harald Niederreiter; Peter J. Shiue
Название: Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
ISBN: 0387945776 ISBN-13(EAN): 9780387945774
Издательство: Springer
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Цена: 111790.00 T
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Описание: Scientists and engineers are increasingly making use of simulation methods to solve problems which are insoluble by analytical techniques. Monte Carlo methods which make use of probabilistic simulations are frequently used in areas such as numerical integration, complex scheduling, queueing networks, and large-dimensional simulations.

Автор: Pierre L` Ecuyer; Art B. Owen
Название: Monte Carlo and Quasi-Monte Carlo Methods 2008
ISBN: 364204106X ISBN-13(EAN): 9783642041068
Издательство: Springer
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Цена: 194730.00 T
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Описание: This volume represents the refereed proceedings of the Eighth International C- ference on Monte Carlo and Quasi-Monte Carlo Methods in Scienti c Computing, which was held at the University of Montr al, from 6-11 July, 2008. It contains a limited selection of articles based on presentations made at the conference. The program was arranged with the help of an international committee consisting of: Ronald Cools, Katholieke Universiteit Leuven Luc Devroye, McGill University Henri Faure, CNRS Marseille Paul Glasserman, Columbia University Peter W. Glynn, Stanford University Stefan Heinrich, University of Kaiserslautern Fred J. Hickernell, Illinois Institute of Technology Aneta Karaivanova, Bulgarian Academy of Science Alexander Keller, mental images GmbH, Berlin Adam Kolkiewicz, University of Waterloo Frances Y. Kuo, University of New South Wales Christian L cot, Universit de Savoie, Chamb ry Pierre L'Ecuyer, Universit de Montr al (Chair and organizer) Jun Liu, Harvard University Peter Math , Weierstrass Institute Berlin Makoto Matsumoto, Hiroshima University Thomas M ller-Gronbach, Otto von Guericke Universit t Harald Niederreiter, National University of Singapore Art B. Owen, Stanford University Gilles Pag s, Universit Pierre et Marie Curie (Paris 6) Klaus Ritter, TU Darmstadt Karl Sabelfeld, Weierstrass Institute Berlin Wolfgang Ch. Schmid, University of Salzburg Ian H. Sloan, University of New South Wales Jerome Spanier, University of California, Irvine Bruno Tuf n, IRISA-INRIA, Rennes Henryk Wozniak owski, Columbia University. v vi Preface The local arrangements (program production, publicity, web site, registration, social events, etc.

Автор: Pierre L` Ecuyer; Art B. Owen
Название: Monte Carlo and Quasi-Monte Carlo Methods 2008
ISBN: 3642425240 ISBN-13(EAN): 9783642425240
Издательство: Springer
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Цена: 194730.00 T
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Описание: Tutorials.- Monte Carlo and Quasi-Monte Carlo for Statistics.- Monte Carlo Computation in Finance.- Invited Articles.- Particle Markov Chain Monte Carlo for Efficient Numerical Simulation.- Computational Complexity of Metropolis-Hastings Methods in High Dimensions.- On Quasi-Monte Carlo Rules Achieving Higher Order Convergence.- Sensitivity Estimates for Compound Sums.- New Perspectives on (0, )-Sequences.- Variable Subspace Sampling and Multi-level Algorithms.- Markov Chain Monte Carlo Algorithms: Theory and Practice.- MINT - New Features and New Results.- Contributed Articles.- Recursive Computation of Value-at-Risk and Conditional Value-at-Risk using MC and QMC.- Adaptive Monte Carlo Algorithms Applied to Heterogeneous Transport Problems.- Efficient Simulation of Light-Tailed Sums: an Old-Folk Song Sung to a Faster New Tune....- Distribution of Digital Explicit Inversive Pseudorandom Numbers and Their Binary Threshold Sequence.- Extensions of Fibonacci Lattice Rules.- Efficient Search for Two-Dimensional Rank-1 Lattices with Applications in Graphics.- Parallel Random Number Generators Based on Large Order Multiple Recursive Generators.- Efficient Numerical Inversion for Financial Simulations.- Equidistribution Properties of Generalized Nets and Sequences.- Implementation of a Component-By-Component Algorithm to Generate Small Low-Discrepancy Samples.- Quasi-Monte Carlo Simulation of Diffusion in a Spatially Nonhomogeneous Medium.- Discrepancy of Two-Dimensional Digitally Shifted Hammersley Point Sets in Base.- Vibrato Monte Carlo Sensitivities.- The Weighted Variance Minimization in Jump-Diffusion Stochastic Volatility Models.- -Nets and Maximized Minimum Distance, Part II.- Automation of Statistical Tests on Randomness to Obtain Clearer Conclusion.- On Subsequences of Niederreiter-Halton Sequences.- Correcting the Bias in Monte Carlo Estimators of American-style Option Values.- Fast Principal Components Analysis Method for Finance Problems With Unequal Time Steps.- Adaptive Monte Carlo Algorithms for General Transport Problems.- On Array-RQMC for Markov Chains: Mapping Alternatives and Convergence Rates.- Testing the Tests: Using Random Number Generators to Improve Empirical Tests.- Stochastic Spectral Formulations for Elliptic Problems.- Adaptive (Quasi-)Monte Carlo Methods for Pricing Path-Dependent Options.- Monte Carlo Simulation of Stochastic Integrals when the Cost of Function Evaluation Is Dimension Dependent.- Recent Progress in Improvement of Extreme Discrepancy and Star Discrepancy of One-Dimensional Sequences.- Discrepancy of Hyperplane Nets and Cyclic Nets.- A PRNG Specialized in Double Precision Floating Point Numbers Using an Affine Transition.- On the Behavior of the Weighted Star Discrepancy Bounds for Shifted Lattice Rules.- Ergodic Estimations of Upscaled Coefficients for Diffusion in Random Velocity Fields.- Green's Functions by Monte Carlo.- Tractability of Multivariate Integration for Weighted Korobov Spaces: My 15 Year Partnership with Ian Sloan