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Monte Carlo Statistical Methods, Christian Robert; George Casella


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Цена: 16769.00р.
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Автор: Christian Robert; George Casella   (Кристиан Роберт, Джордж Казелл)
Название:  Monte Carlo Statistical Methods
Перевод названия: Кристиан Роберт, Джордж Казелла: Статистические методы Монте-Карло
ISBN: 9781441919397
Издательство: Springer
Классификация:


ISBN-10: 1441919392
Обложка/Формат: Paperback
Страницы: 649
Вес: 0.94 кг.
Дата издания: 29.11.2010
Серия: Springer Texts in Statistics
Язык: English
Размер: 234 x 158 x 36
Основная тема: Statistics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.


The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Monte Carlo Methods in Financial Engineering

Автор: Glasserman
Название: Monte Carlo Methods in Financial Engineering
ISBN: 0387004513 ISBN-13(EAN): 9780387004518
Издательство: Springer
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Цена: 11179.00 р.
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Описание: From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not."

Statistical Learning for Biomedical Data

Автор: Malley
Название: Statistical Learning for Biomedical Data
ISBN: 0521699096 ISBN-13(EAN): 9780521699099
Издательство: Cambridge Academ
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Цена: 6494.00 р.
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Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.

Mean Field Simulation for Monte Carlo Integration

Автор: Del Moral
Название: Mean Field Simulation for Monte Carlo Integration
ISBN: 1138198730 ISBN-13(EAN): 9781138198739
Издательство: Taylor&Francis
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Цена: 7961.00 р.
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Описание:

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters.

Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle simulation models and interdisciplinary research topics, including interacting jumps and McKean-Vlasov processes, sequential Monte Carlo methodologies, genetic particle algorithms, genealogical tree-based algorithms, and quantum and diffusion Monte Carlo methods.

Along with covering refined convergence analysis on nonlinear Markov chain models, the author discusses applications related to parameter estimation in hidden Markov chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty propagations in numerical codes, rare event simulation, financial mathematics, and free energy and quasi-invariant measures arising in computational physics and population biology.

This book shows how mean field particle simulation has revolutionized the field of Monte Carlo integration and stochastic algorithms. It will help theoretical probability researchers, applied statisticians, biologists, statistical physicists, and computer scientists work better across their own disciplinary boundaries.

Statistical models and methods for financial markets

Автор: Lai, Tze Leung Xing, Haipeng
Название: Statistical models and methods for financial markets
ISBN: 1441926682 ISBN-13(EAN): 9781441926685
Издательство: Springer
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Цена: 10335.00 р.
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Описание: The authors here present statistical methods and models of importance to quantitative finance and links finance theory to market practice via statistical modeling and decision making. They provide basic statistical background as well as in-depth applications.

Markov Chain Monte Carlo

Автор: Gamerman, Dani.
Название: Markov Chain Monte Carlo
ISBN: 1584885874 ISBN-13(EAN): 9781584885870
Издательство: Taylor&Francis
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Цена: 15312.00 р.
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Описание: Incorporating changes in theory and highlighting various applications, this book presents a comprehensive introduction to the methods of Markov Chain Monte Carlo (MCMC) simulation technique. It incorporates the developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection.

Applied Linear Statistical Models with Student CD

Автор: Nachtsheim;Neter;Kutner
Название: Applied Linear Statistical Models with Student CD
ISBN: 0071122214 ISBN-13(EAN): 9780071122214
Издательство: McGraw-Hill
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Цена: 9265.00 р.
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Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

An Introduction to Multivariate Statistical Analysis, Third Edition

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: 27712.00 р.
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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.

Research design and statistical analysis

Автор: Myers, Jerome L
Название: Research design and statistical analysis
ISBN: 0805864318 ISBN-13(EAN): 9780805864311
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: This interdisciplinary group of scholars-anthropologists, archaeologists, architects, educators, lawyers, heritage administrators, policy analysts, and consultants-make the first attempt to define and assess heritage values on a local, national and global level. Chapters range from the theoretical to policy frameworks to case studies of heritage practice, written by scholars from eight countries.

Essential Statistical Methods for Medical Statistics,

Автор: J. Philip Miller
Название: Essential Statistical Methods for Medical Statistics,
ISBN: 0444537376 ISBN-13(EAN): 9780444537379
Издательство: Elsevier Science
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Цена: 8541.00 р.
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Описание: Addresses statistical challenges in epidemiological, biomedical, and pharmaceutical research. This book presents methods for assessing Biomarkers, analysis of competing risks. It offers clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs.

Statistical Methods in Biology: Desing and Analysis of Experiments and Regression 1st Edition, S.J.Welham, S.A. Gezan, S.J. Clark, A. Mead.- Chapman and Hall/CRC; 1 edition (August 22, 2014), 608 pages, Hardover

Название: Statistical Methods in Biology: Desing and Analysis of Experiments and Regression 1st Edition, S.J.Welham, S.A. Gezan, S.J. Clark, A. Mead.- Chapman and Hall/CRC; 1 edition (August 22, 2014), 608 pages, Hardover
ISBN: 1439808783 ISBN-13(EAN): 9781439808788
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание:

Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience.

Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.

By the time you reach the end of the book (and online material) you will have gained:

  • A clear appreciation of the importance of a statistical approach to the design of your experiments,
  • A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
  • Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
  • An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.

The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.


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