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Graphical Data Analysis with R, Unwin


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Цена: 11482.00р.
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Автор: Unwin
Название:  Graphical Data Analysis with R
ISBN: 9781498715232
Издательство: Taylor&Francis
Классификация:


ISBN-10: 1498715230
Обложка/Формат: Hardback
Страницы: 310
Вес: 0.68 кг.
Дата издания: 12.05.2015
Серия: Chapman & hall/crc the r series
Язык: English
Иллюстрации: 2 tables, black and white; 135 illustrations, color
Размер: 244 x 165 x 19
Читательская аудитория: General (us: trade)
Ключевые слова: Probability & statistics, MATHEMATICS / Probability & Statistics / General,REFERENCE / General
Основная тема: Statistical Computing
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

See How Graphics Reveal Information

Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA.

Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.




Probabilistic Graphical Models: Principles and Techniques

Автор: Koller Daphne, Friedman Nir
Название: Probabilistic Graphical Models: Principles and Techniques
ISBN: 0262013193 ISBN-13(EAN): 9780262013192
Издательство: MIT Press
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Цена: 21161.00 р.
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Описание:

A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.

Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.

Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

Graphical models in applied multivariate statistics

Автор: Whittaker, Joe
Название: Graphical models in applied multivariate statistics
ISBN: 0470743662 ISBN-13(EAN): 9780470743669
Издательство: Wiley
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Цена: 10605.00 р.
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Описание: - It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.

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.

Categorical Data Analysis

Автор: Agresti Alan
Название: Categorical Data Analysis
ISBN: 0470463635 ISBN-13(EAN): 9780470463635
Издательство: Wiley
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Цена: 20109.00 р.
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Описание: Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis. " Statistics in Medicine "It is a total delight reading this book.

Analysis of longitudinal data

Название: Analysis of longitudinal data
ISBN: 0199676755 ISBN-13(EAN): 9780199676750
Издательство: Oxford Academ
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Цена: 8395.00 р.
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Описание: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.

Data Reduction And Error Analysis For The Physical Sciences

Автор: Bevington; Robinson
Название: Data Reduction And Error Analysis For The Physical Sciences
ISBN: 0071199268 ISBN-13(EAN): 9780071199261
Издательство: McGraw-Hill
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Цена: 7377.00 р.
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Описание: Provides an introduction to the concepts of statistical analysis of data for students at undergraduate and graduate level. This text also provides tools for data reduction and error analysis commonly required in the physical sciences. It features a variety of numerical and graphical techniques, and emphasizes methods of handling data than theory.

Bayesian Data Analysis, Third Edition

Автор: Gelman
Название: Bayesian Data Analysis, Third Edition
ISBN: 1439840954 ISBN-13(EAN): 9781439840955
Издательство: Taylor&Francis
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Цена: 11088.00 р.
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Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Graphical Models for Security

Автор: Kordy
Название: Graphical Models for Security
ISBN: 3319462628 ISBN-13(EAN): 9783319462622
Издательство: Springer
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Цена: 5870.00 р.
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Описание: This book constitutes the refereed proceedings from the Third International Workshop on Graphical Models for Security, GraMSec 2016, held in Lisbon, Portugal, in June 2016. GraMSec contributes to the development of well-founded graphical security models, efficient algorithms for their analysis, as well as methodologies for their practical usage.

Developing Churn Models Using Data Mining Techniques And Social Network Analysis

Автор: Klepac, Kopal & Mrsic
Название: Developing Churn Models Using Data Mining Techniques And Social Network Analysis
ISBN: 1466662883 ISBN-13(EAN): 9781466662889
Издательство: Mare Nostrum (Eurospan)
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Цена: 27027.00 р.
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Описание: Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios.Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.

Analysis of Multivariate and High-Dimensional Data

Автор: Koch
Название: Analysis of Multivariate and High-Dimensional Data
ISBN: 0521887933 ISBN-13(EAN): 9780521887939
Издательство: Cambridge Academ
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Цена: 10613.00 р.
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Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.

Methods of Microarray Data Analysis II: Papers from CAMDA `01

Автор: Simon M. Lin (Editor), Kimberly F. Johnson
Название: Methods of Microarray Data Analysis II: Papers from CAMDA `01
ISBN: 1475788312 ISBN-13(EAN): 9781475788310
Издательство: Springer
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Цена: 13974.00 р.
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Описание: In a single reference, readers can learn about the most up-to-date methods, ranging from data normalization, feature selection, and discriminative analysis to machine learning techniques. Methods of Microarray Data Analysis II focuses on a single data set, using a different method of analysis in each chapter.

Statistical Analysis of Financial Data in R

Автор: Carmona, Rene
Название: Statistical Analysis of Financial Data in R
ISBN: 1461487870 ISBN-13(EAN): 9781461487876
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Addressing the most challenging issues faced by financial engineers, this book shows how sophisticated mathematics and modern statistical techniques can be used in concrete financial problems. Includes practical examples solved in the R computing environment.


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