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Top r books mentioned on stackoverflow.com

Design Patterns

Ralph Johnson, Erich Gamma, John Vlissides, Richard Helm

Capturing a wealth of experience about the design of object-oriented software, four top-notch designers present a catalog of simple and succinct solutions to commonly occurring design problems. Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves. The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk. 0201633612B07092001

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Clean Code

Robert C. Martin

An extremely pragmatic method for writing better code from the start, and ultimately producing more robust applications.

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Code Complete

Steve McConnell

Features the best practices in the art and science of constructing software--topics include design, applying good techniques to construction, eliminating errors, planning, managing construction activities, and relating personal character to superior software. Original. (Intermediate)

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Accelerated C++

Andrew Koenig, Barbara E. Moo

Takes a practical approach to solving problems using C++. This book describes real problems and solutions, not just language features. It covers the language and standard library together.

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Language Implementation Patterns

Terence Parr

A guide to language implementation covers such topics as data readers, model-driven code generators, source-to-source translators, and source analyzers.

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Pattern classification

Richard O. Duda, Peter E. Hart, David G. Stork

This edition has been completely revised, enlarged and formatted in two colour. It is a systematic account of the major topics in pattern recognition, based on the fundamental principles. It includes extensive examples, exercises and a solutions manual.

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The Visual Display of Quantitative Information

Edward R. Tufte

Graphical practice. Theory of data graphics.

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ggplot2

Hadley Wickham

Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures

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The Grammar of Graphics

Leland Wilkinson

This book was written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data. It presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. This foundation was designed for a distributed computing environment (Internet, Intranet, client-server), with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library (GPL) developed in collaboration with Dan Rope and Dan Carr, this book focuses on the deep structures involved in producing quantitative graphics from data. What are the rules that underly the production of pie charts, bar charts, scatterplots, function plots, maps, mosaics, radar charts? These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics. Those less interested in the theoretical and mathematical foundations can still get a sense of the richness and structure of the system by examining the numerous and often unique color graphics it can produce. Leland Wilkinson is Senior VP, SYSTAT Products at SPSS Inc. and Adjunct Professor of Statistics at Northwestern University. He wrote the SYSTAT statistical package and founded SYSTAT Inc. in 1984. Wilkinson joined SPSS in a 1994 acquisition and now works on research and development of graphical applications for data mining and statistics. He is a Fellow of the ASA and an Associate Editor of The American Statistician. In addition to journal articles and theoriginal SYSTAT computer program and manuals, Wilkinson is the author (with Grant Blank and Chris Gruber) of Desktop Data Analysis with SYSTAT.

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Software for Data Analysis

John Chambers

John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.

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The Clean Coder

Robert C. Martin

Presents practical advice on the disciplines, techniques, tools, and practices of computer programming and how to approach software development with a sense of pride, honor, and self-respect.

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Data Mining

Ian H. Witten, Eibe Frank, Mark Andrew Hall

Provides information on the tools and techniques of data mining, covering such topics as data transformation, ensemble learning, and datasets, and presents instructions on the Weka machine learning software.

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Information Dashboard Design

Stephen Few

Dashboards have become popular in recent years as uniquely powerful tools for communicating important information at a glance. Although dashboards are potentially powerful, this potential is rarely realized. The greatest display technology in the world won't solve this if you fail to use effective visual design. And if a dashboard fails to tell you precisely what you need to know in an instant, you'll never use it, even if it's filled with cute gauges, meters, and traffic lights. Don't let your investment in dashboard technology go to waste. This book will teach you the visual design skills you need to create dashboards that communicate clearly, rapidly, and compellingly. Information Dashboard Design will explain how to: Avoid the thirteen mistakes common to dashboard design Provide viewers with the information they need quickly and clearly Apply what we now know about visual perception to the visual presentation of information Minimize distractions, cliches, and unnecessary embellishments that create confusion Organize business information to support meaning and usability Create an aesthetically pleasing viewing experience Maintain consistency of design to provide accurate interpretation Optimize the power of dashboard technology by pairing it with visual effectiveness Stephen Few has over 20 years of experience as an IT innovator, consultant, and educator. As Principal of the consultancy Perceptual Edge, Stephen focuses on data visualization for analyzing and communicating quantitative business information. He provides consulting and training services, speaks frequently at conferences, and teaches in the MBA program at the University of California in Berkeley. He is also the author of Show Me the Numbers: Designing Tables and Graphs to Enlighten. Visit his website at www.perceptualedge.com.

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Applied Econometrics with R

Christian Kleiber, Achim Zeileis

R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

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R Graphics

Paul Murrell

R is revolutionizing the world of statistical computing. Powerful, flexible, and best of all free, R is now the program of choice for tens of thousands of statisticians. Destined to become an instant classic, R Graphics presents the first complete, authoritative exposition on the R graphical system. Paul Murrell, widely known as the leading expert on R graphics, has developed an in-depth resource that takes nothing for granted and helps both neophyte and seasoned users master the intricacies of R graphics. After an introductory overview of R graphics facilities, the presentation first focuses on the traditional graphics system, showing how to work the traditional functions, describing functions that are available to produce complete plots, and how to customize the details of plots. The second part of the book describes the grid graphics system - a system unique to R and much more powerful than the traditional system. The author, who was integral in the development of the grid system, shows, starting from a blank page, how it can be used to produce graphical scenes. He also describes how to develop new graphical functions that are easy for others to use and build on. Appendices contain a brief introduction to the R system in general and discuss how the traditional and grid graphics systems can be combined. Much of the information presented in this book cannot be found anywhere else. Well ahead of the curve, particularly regarding the grid system, R Graphics will have a major impact on the future direction of statistical graphics development. The author maintains a website with more information.

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The Art of R Programming

Norman Matloff

A guide to software development using the R programming language covers such topics as closures, recursion, anonymous functions, and debugging techniques.

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Applied Predictive Modeling

Max Kuhn, Kjell Johnson

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance—all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code for each step of the process. The data sets and corresponding code are available in the book’s companion AppliedPredictiveModeling R package, which is freely available on the CRAN archive. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. Readers and students interested in implementing the methods should have some basic knowledge of R. And a handful of the more advanced topics require some mathematical knowledge.

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Semiology of Graphics

Jacques Bertin, William J. Berg

Originally published in French in 1967, "Semiology of Graphics" holds a significant place in the theory of information design. It presents a close study of graphic techniques including shape, orientation, color, texture, volume, and size in an array of more than 1,000 maps and diagrams.

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Simulation Modeling and Analysis

Averill M. Law

Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the "bible" of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: *A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. *A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. *An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).

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An R Companion to Applied Regression

John Fox, Sanford Weisberg

This book aims to provide a broad introduction to the R statistical environment in the context of applied regression analysis, which is typically studied by social scientists and others in a second course in applied statistics.

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R Graphics Cookbook

Winston Chang

"Practical recipes for visualizing data"--Cover.

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R in a Nutshell

Joseph Adler

Presents a guide to the R computer language, covering such topics as the user interface, packages, syntax, objects, functions, object-oriented programming, data sets, lattice graphics, regression models, and bioconductor.

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Software for Data Analysis

John Chambers

John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.

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Head First Statistics

Dawn Griffiths

"Head First Statistics" brings a typically difficult subject to life, teaching readers everything they want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples.

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Dynamic Linear Models with R

Giovanni Petris, Sonia Petrone, Patrizia Campagnoli

State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.

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Data Manipulation with R

Phil Spector

This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data. In addition to the built-in functions, a number of readily available packages from CRAN (the Comprehensive R Archive Network) are also covered. All of the methods presented take advantage of the core features of R: vectorization, efficient use of subscripting, and the proper use of the varied functions in R that are provided for common data management tasks. Most experienced R users discover that, especially when working with large data sets, it may be helpful to use other programs, notably databases, in conjunction with R. Accordingly, the use of databases in R is covered in detail, along with methods for extracting data from spreadsheets and datasets created by other programs. Character manipulation, while sometimes overlooked within R, is also covered in detail, allowing problems that are traditionally solved by scripting languages to be carried out entirely within R. For users with experience in other languages, guidelines for the effective use of programming constructs like loops are provided. Since many statistical modeling and graphics functions need their data presented in a data frame, techniques for converting the output of commonly used functions to data frames are provided throughout the book.

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Applied Spatial Data Analysis with R

Roger S. Bivand, Edzer J. Pebesma, Virgilio Gómez-Rubio

This book addresses the needs of researchers and students using R to analyze spatial data across a range of disciplines and professions. The book is co-authored by a group involved in the Comprehensive R Archive Network.

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Complex Surveys

Thomas Lumley

A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.

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Modern Applied Statistics with S

W.N. Venables, B.D. Ripley

A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.

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