Computer Intensive Statistical Methods, Hjorth, J. S. Urban.

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: 69870.00 T
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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.

Автор: James Gareth
Название: An Introduction to Statistical Learning
ISBN: 1461471370 ISBN-13(EAN): 9781461471370
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Невозможна поставка.
Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.

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: 60190.00 T
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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.

Автор: Hjorth
Название: Computer Intensive Statistical Methods
ISBN: 0412491605 ISBN-13(EAN): 9780412491603
Издательство: Taylor&Francis
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Цена: 183750.00 T
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Описание: This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome obstacles that could not be previously solved by methods such as regression and time series modelling in the areas of economics, meteorology, and transportation.

Автор: Agarwal
Название: Statistical Methods for Recommender Systems
ISBN: 1107036070 ISBN-13(EAN): 9781107036079
Издательство: Cambridge Academ
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Цена: 50680.00 T
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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.

Автор: Helmut Rieder
Название: Robust Statistics, Data Analysis, and Computer Intensive Methods
ISBN: 0387946608 ISBN-13(EAN): 9780387946603
Издательство: Springer
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Цена: 111790.00 T
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Описание: This text presents a collection of contributions on modern techniques which are becoming widely used in statistics. These methods include the bootstrap, nonparametric density estimation, robust regression, and projections and sections.

Автор: Wolfgang H?rdle; L?opold Simar
Название: Computer Intensive Methods in Statistics
ISBN: 3790806773 ISBN-13(EAN): 9783790806779
Издательство: Springer
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Цена: 81050.00 T
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Описание: A detailed exploration of statistical computer methods, including Bayesian computing, interfacing statistics, image analysis and resampling methods. The text explains how graphical interaction on modern statistical environments has provided the possibility of deeper insights into statistics.

Автор: Zwanzig, Silvelyn (uppsala University, Sweden) Mahjani, Behrang (uppsala University, Sweden)
Название: Computer intensive methods in statistics
ISBN: 0367194236 ISBN-13(EAN): 9780367194239
Издательство: Taylor&Francis
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Цена: 59190.00 T
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Описание: This book gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, wavelet estimators, splines, and model assessment

Автор: Zwanzig, Silvelyn , Mahjani, Behrang
Название: Computer Intensive Methods in Statistics
ISBN: 0367194252 ISBN-13(EAN): 9780367194253
Издательство: Taylor&Francis
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Цена: 163330.00 T
Наличие на складе: Невозможна поставка.
Описание: This book gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, wavelet estimators, splines, and model assessment

Автор: Little
Название: Statistical Analysis with Missing Data, Third Edit ion
ISBN: 0470526793 ISBN-13(EAN): 9780470526798
Издательство: Wiley
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Цена: 84430.00 T
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Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.

Автор: Marco Corazza; Cira Perna; Marilena Sibillo; Flore
Название: Mathematical and Statistical Methods for Actuarial Sciences and Finance
ISBN: 3319502336 ISBN-13(EAN): 9783319502335
Издательство: Springer
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Цена: 93160.00 T
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Описание: This volume gathers selected peer-reviewed papers presented at the "International MAF Conference 2016 - Mathematical and Statistical Methods for Actuarial Sciences and Finance" held in Paris at the University of Paris-Dauphine from March 30 to April 1, 2016.