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Computational Bayesian Statistics: An Introduction, M. Antonia Amaral Turkman, Carlos Daniel Paulino, Peter Muller


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Цена: 17424.00р.
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Автор: M. Antonia Amaral Turkman, Carlos Daniel Paulino, Peter Muller
Название:  Computational Bayesian Statistics: An Introduction
ISBN: 9781108481038
Издательство: Cambridge Academ
Классификация:




ISBN-10: 1108481035
Обложка/Формат: Hardback
Страницы: 254
Вес: 0.48 кг.
Дата издания: 28.02.2019
Серия: Institute of mathematical statistics textbooks
Язык: English
Иллюстрации: Worked examples or exercises; 00 printed music items; 00 tables, unspecified; 00 tables, color; 00 tables, black and white; 00 plates, unspecified; 00 plates, color; 00 plates, black and white; 00 maps; 00 halftones, unspecified; 00 halftones, color;
Размер: 235 x 156 x 17
Читательская аудитория: Professional and scholarly
Ключевые слова: Data analysis: general,Machine learning,Probability & statistics,Economic statistics, COMPUTERS / Natural Language Processing
Подзаголовок: An introduction
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This book explains the fundamental ideas of Bayesian analysis, with a focus on computational methods such as MCMC and available software such as R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX. It is suitable as a textbook for a first graduate-level course and as a user`s guide for researchers and graduate students from beyond statistics.


Introduction to Econometrics, 5 ed.

Автор: Dougherty Christopher
Название: Introduction to Econometrics, 5 ed.
ISBN: 0199676828 ISBN-13(EAN): 9780199676828
Издательство: Oxford Academ
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Цена: 12037.00 р.
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Описание: Combining the rigour of econometric theory with an accessible style, Dougherty`s step by step explanations and relevant practical exercises ensure students develop an intuitive understanding of econometrics, and gain hands-on experience of the tools used in economic and financial forecasting.

An Introduction To Computational Ri

Автор: Feng
Название: An Introduction To Computational Ri
ISBN: 1498742165 ISBN-13(EAN): 9781498742160
Издательство: Taylor&Francis
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Цена: 17609.00 р.
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Описание: The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development. Today's computational power and technology make it possible for the life insurance industry to develop highly sophisticated models, which were impossible just a decade ago. Nonetheless, as more industrial practices and regulations move towards dependence on stochastic models, the demand for computational power continues to grow. While the industry continues to rely heavily on hardware innovations, trying to make brute force methods faster and more palatable, we are approaching a crossroads about how to proceed. An Introduction to Computational Risk Management of Equity-Linked Insurance provides a resource for students and entry-level professionals to understand the fundamentals of industrial modeling practice, but also to give a glimpse of software methodologies for modeling and computational efficiency. Features Provides a comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance with exercises and programming samples Includes a collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematicians Summarizes state-of-arts computational techniques for risk management professionals Bridges the gap between the latest developments in finance and actuarial literature and the practice of risk management for investment-combined life insurance Gives a comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methods Runhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow. Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.

Introduction To Functional Data Ana

Автор: Kokoszka
Название: Introduction To Functional Data Ana
ISBN: 1498746349 ISBN-13(EAN): 9781498746342
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: The book provides an introduction to functional data analysis (FDA), useful to students and researchers. FDA is now generally viewed as a fundamental subfield of statistics. FDA methods have been applied to science, business and engineering.

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

Автор: Scott M. Lynch
Название: Introduction to Applied Bayesian Statistics and Estimation for Social Scientists
ISBN: 1441924345 ISBN-13(EAN): 9781441924346
Издательство: Springer
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Цена: 21661.00 р.
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Описание: The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.

Computational Statistics Handbook with MATLAB

Автор: Martinez Wendy L.
Название: Computational Statistics Handbook with MATLAB
ISBN: 1466592737 ISBN-13(EAN): 9781466592735
Издательство: Taylor&Francis
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Цена: 16078.00 р.
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Описание:

A Strong Practical Focus on Applications and Algorithms
Computational Statistics Handbook with MATLAB(R), Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods.

New to the Third Edition
This third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines.

Web Resource
The authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.

Introduction to High-Dimensional Statistics

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 9645.00 р.
Наличие на складе: Поставка под заказ.

Описание: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.

Barron`s AP Statistics, 8th Edition

Автор: Sternstein Martin
Название: Barron`s AP Statistics, 8th Edition
ISBN: 1438004982 ISBN-13(EAN): 9781438004983
Издательство: Ingram
Цена: 2619.00 р.
Наличие на складе: Нет в наличии.

Описание: This manual s in-depth preparation for the AP Statistics exam features the 35 absolutely best AP Statistics exam hints found anywhere, and includes:

  • A diagnostic test and five full-length and up-to-date practice exams
  • All test questions answered and explained
  • Additional multiple-choice and free-response questions with answers
  • A 15-chapter subject review covering all test topics
  • A guide to basic uses of TI-83/TI-84 calculators
    The manual can be purchased alone or with an enclosed CD-ROM that presents two additional practice tests with automatic scoring of the multiple-choice questions, as well as a second CD-ROM introducing the TI-Nspire.
    BONUS ONLINE PRACTICE TEST Students who purchase this book or package will also get FREE access to one additional full-length online AP Statistics test with all questions answered and explained."
  • Understanding Computational Bayesian Statistics

    Автор: Bolstad
    Название: Understanding Computational Bayesian Statistics
    ISBN: 0470046090 ISBN-13(EAN): 9780470046098
    Издательство: Wiley
    Рейтинг:
    Цена: 20267.00 р.
    Наличие на складе: Есть у поставщика Поставка под заказ.

    Описание: A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach.

    Introduction to Bayesian Statistics

    Автор: Karl-Rudolf Koch
    Название: Introduction to Bayesian Statistics
    ISBN: 3642091830 ISBN-13(EAN): 9783642091834
    Издательство: Springer
    Рейтинг:
    Цена: 16977.00 р.
    Наличие на складе: Есть у поставщика Поставка под заказ.

    Описание: This book presents Bayes` theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters.

    Introduction to Probability, Second Edition

    Автор: Joseph K. Blitzstein, Jessica Hwang
    Название: Introduction to Probability, Second Edition
    ISBN: 1138369918 ISBN-13(EAN): 9781138369917
    Издательство: Taylor&Francis
    Рейтинг:
    Цена: 11176.00 р.
    Наличие на складе: Есть у поставщика Поставка под заказ.

    Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

    Computational statistics in the earth sciences :

    Автор: Chave, Alan Dana.
    Название: Computational statistics in the earth sciences :
    ISBN: 1107096006 ISBN-13(EAN): 9781107096004
    Издательство: Cambridge Academ
    Рейтинг:
    Цена: 11563.00 р.
    Наличие на складе: Поставка под заказ.

    Описание: Based on a course taught by the author, this book combines theoretical underpinnings of statistics with practical analysis of Earth sciences data using MATLAB. Datasets and bespoke MATLAB scripts are available online, as well as questions for use by instructors. This is an ideal text for advanced undergraduate and graduate students.

    Introduction to the New Statistics

    Автор: Cumming, Geoff.
    Название: Introduction to the New Statistics
    ISBN: 1138825522 ISBN-13(EAN): 9781138825529
    Издательство: Taylor&Francis
    Рейтинг:
    Цена: 9951.00 р.
    Наличие на складе: Поставка под заказ.

    Описание: This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.


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