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Statistical Simulation, Headrick


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Цена: 10717.00р.
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Автор: Headrick
Название:  Statistical Simulation
ISBN: 9781138116283
Издательство: Taylor&Francis
Классификация:
ISBN-10: 1138116289
Обложка/Формат: Paperback
Страницы: 174
Вес: 0.33 кг.
Дата издания: 14.06.2017
Язык: English
Иллюстрации: 141 tables, black and white; 6 illustrations, black and white
Размер: 235 x 159
Читательская аудитория: General (us: trade)
Ключевые слова: Probability & statistics, MATHEMATICS / Probability & Statistics / General,MATHEMATICS / Probability & Statistics / Bayesian Analysis
Основная тема: Statistical Theory & Methods
Подзаголовок: Power Method Polynomials and Other Transformations
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Although power method polynomials based on the standard normal distributions have been used in many different contexts for the past 30 years, it was not until recently that the probability density function (pdf) and cumulative distribution function (cdf) were derived and made available. Focusing on both univariate and multivariate nonnormal data generation, Statistical Simulation: Power Method Polynomials and Other Transformations presents techniques for conducting a Monte Carlo simulation study. It shows how to use power method polynomials for simulating univariate and multivariate nonnormal distributions with specified cumulants and correlation matrices.

The book first explores the methodology underlying the power method, before demonstrating this method through examples of standard normal, logistic, and uniform power method pdfs. It also discusses methods for improving the performance of a simulation based on power method polynomials. The book then develops simulation procedures for systems of linear statistical models, intraclass correlation coefficients, and correlated continuous variates and ranks. Numerical examples and results from Monte Carlo simulations illustrate these procedures. The final chapter describes how the g-and-h and generalized lambda distribution (GLD) transformations are special applications of the more general multivariate nonnormal data generation approach. Throughout the text, the author employs Mathematica(R) in a range of procedures and offers the source code for download online.

Written by a longtime researcher of the power method, this book explains how to simulate nonnormal distributions via easy-to-use power method polynomials. By using the methodology and techniques developed in the text, readers can evaluate different transformations in terms of comparing percentiles, measures of central tendency, goodness-of-fit tests, and more.




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.

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.

Topics in Statistical Simulation

Автор: V.B. Melas; Stefania Mignani; Paola Monari; Luigi
Название: Topics in Statistical Simulation
ISBN: 1493921037 ISBN-13(EAN): 9781493921034
Издательство: Springer
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Цена: 16769.00 р.
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Описание: The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation.

Topics in Statistical Simulation

Автор: V.B. Melas; Stefania Mignani; Paola Monari; Luigi
Название: Topics in Statistical Simulation
ISBN: 1493947842 ISBN-13(EAN): 9781493947843
Издательство: Springer
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Цена: 16769.00 р.
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Описание: The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation.

Statistical Methods for Recommender Systems

Автор: Agarwal
Название: Statistical Methods for Recommender Systems
ISBN: 1107036070 ISBN-13(EAN): 9781107036079
Издательство: Cambridge Academ
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Цена: 7602.00 р.
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Описание: Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.

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.

Vorticity, Statistical Mechanics, and Monte Carlo Simulation

Автор: Chjan Lim; Joseph Nebus
Название: Vorticity, Statistical Mechanics, and Monte Carlo Simulation
ISBN: 1441922474 ISBN-13(EAN): 9781441922472
Издательство: Springer
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Цена: 20263.00 р.
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Описание: This book is drawn from across many active fields of mathematics and physics. With fresh insights into an important field, the book addresses how to access interesting, original, and publishable research in statistical modeling of large-scale flows and related fields.

Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Statistical and Machine-Learning Data Mining

Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 9033.00 р.
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Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Stochastic Simulation: Algorithms and Analysis

Автор: Asmussen
Название: Stochastic Simulation: Algorithms and Analysis
ISBN: 038730679X ISBN-13(EAN): 9780387306797
Издательство: Springer
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Цена: 6981.00 р.
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Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first  half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of  examples, exercises and applications students, practitioners and researchers in  probability, statistics, operations research, economics, finance, engineering  as well as biology and chemistry and physics will find the book of value.  Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of  Engineering at Stanford University. 

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.


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