- Table View
- List View
R for Programmers: Quantitative Investment Applications
by Dan ZhangAfter the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management.
R for Quantitative Chemistry
by David K. GosserR for Quantitative Chemistry is an exploration of how the R language can be applied to a wide variety of problems in what is typically termed "Quantitative Chemistry" or sometimes "Analytical Chemistry". Topics include: basic statistics, spectroscopic data, acid base equilibria and titrations, binding curves (of great current interest for biomedical applications), Fourier Transforms, and chemical kinetics and enzyme kinetics. An innovative feature is the discussion (as an alternative to the less stable nls packages) of the simplex adaptation subplex (R package) coupled with Monte Carlo analysis to determine confidence intervals for estimated parameters resulting from least squares optimization. Chemists who are interested in learning R as a research tool as well as Chemists who are teaching Quantitative Chemistry, as well as their students will be interested. This book is useful as most R books approach data analysis from an economic, social, medical, or biological context. Analysis of chemical data draws upon specific numerical models and a different set R programming and packages than is typically discussed in other disciplines. This book will be based upon, in large part, actual experimental data and will include end of chapter questions and projects. Readers are encouraged to email the author at gosserch@gmail.com and to follow the accompanying blog on Medium "R Programming for Quantitative Chemistry". Key Features: Elements of R programming for Chemists Literature Based Examples Includes Binding Assay Analysis Integrates theory, experiment, and R programming
R for SAS and SPSS Users
by Robert A. MuenchenThis book introduces R using SAS and SPSS terms. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It compares and contrasts the differing approaches of all three packages.
R for Stata Users
by Robert A. Muenchen Joseph M. HilbeStata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to extend the power of Stata through the use of R. It introduces R using Stata terminology with which you are already familiar. It steps through more than 30 programs written in both languages, comparing and contrasting the two packages' different approaches. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.
R for Statistics
by Pierre-Andre Cornillon Francois Husson Arnaud Guyader Nicolas Jegou Julie Josse Maela Kloareg Eric Matzner-Lober Laurent RouvièreAlthough there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics in
R for the Rest of Us: A Statistics-Free Introduction
by David KeyesLearn how to use R for everything from workload automation and creating online reports, to interpreting data, map making, and more.Written by the founder of a very popular online training platform for the R programming language!The R programming language is a remarkably powerful tool for data analysis and visualization, but its steep learning curve can be intimidating for some. If you just want to automate repetitive tasks or visualize your data, without the need for complex math, R for the Rest of Us is for you.Inside you&’ll find a crash course in R, a quick tour of the RStudio programming environment, and a collection of real-word applications that you can put to use right away. You&’ll learn how to create informative visualizations, streamline report generation, and develop interactive websites—whether you&’re a seasoned R user or have never written a line of R code.You&’ll also learn how to:• Manipulate, clean, and parse your data with tidyverse packages like dplyr and tidyr to make data science operations more user-friendly• Create stunning and customized plots, graphs, and charts with ggplot2 to effectively communicate your data insights• Import geospatial data and write code to produce visually appealing maps automatically• Generate dynamic reports, presentations, and interactive websites with R Markdown and Quarto that seamlessly integrate code, text, and graphics• Develop custom functions and packages tailored to your specific needs, allowing you to extend R&’s functionality and automate complex tasksUnlock a treasure trove of techniques to transform the way you work. With R for the Rest of Us, you&’ll discover the power of R to get stuff done. No advanced statistics degree required.
R für Dummies (Für Dummies)
by Joris Meys Andrie de VriesWollen Sie auch die umfangreichen Möglichkeiten von R nutzen, um Ihre Daten zu analysieren, sind sich aber nicht sicher, ob Sie mit der Programmiersprache wirklich zurechtkommen? Keine Sorge - dieses Buch zeigt Ihnen, wie es geht - selbst wenn Sie keine Vorkenntnisse in der Programmierung oder Statistik haben. Andrie de Vries und Joris Meys zeigen Ihnen Schritt für Schritt und anhand zahlreicher Beispiele, was Sie alles mit R machen können und vor allem wie Sie es machen können. Von den Grundlagen und den ersten Skripten bis hin zu komplexen statistischen Analysen und der Erstellung aussagekräftiger Grafiken. Auch fortgeschrittenere Nutzer finden in diesem Buch viele Tipps und Tricks, die Ihnen die Datenauswertung erleichtern.
R in Action: Data analysis and graphics with R
by Robert I. KabacoffSummaryR in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyBusiness pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you're likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide.About the BookR in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.What's InsideComplete R language tutorialUsing R to manage, analyze, and visualize dataTechniques for debugging programs and creating packagesOOP in ROver 160 graphsAbout the AuthorDr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net.Table of ContentsPART 1 GETTING STARTEDIntroduction to RCreating a datasetGetting started with graphsBasic data managementAdvanced data managementPART 2 BASIC METHODSBasic graphsBasic statisticsPART 3 INTERMEDIATE METHODSRegressionAnalysis of variancePower analysisIntermediate graphsResampling statistics and bootstrappingPART 4 ADVANCED METHODSGeneralized linear modelsPrincipal components and factor analysisTime seriesCluster analysisClassificationAdvanced methods for missing dataPART 5 EXPANDING YOUR SKILLSAdvanced graphics with ggplot2Advanced programmingCreating a packageCreating dynamic reportsAdvanced graphics with the lattice package available online only from manning.com/kabacoff2
R in Projekten anwenden für Dummies (Für Dummies)
by Joseph SchmullerDieses Buch bietet einen einzigartigen Learning-by-Doing-Ansatz. Sie werden Ihre R-Fähigkeiten erweitern und vertiefen, indem Sie eine Vielzahl von Beispielprojekten aus der Praxis nachvollziehen. Erlernen Sie die Grundlagen von R und RStudio sowie Möglichkeiten der Datenreduktion, des Mapping und der Bildverarbeitung. Dabei kommen Werkzeuge zum Einsatz, die Daten grafisch auswerten, die Analyse interaktiv machen oder die maschinelles Lernen einsetzen. Und auf dem Weg dahin können Sie sogar Ihr Statistikwissen noch erweitern. Warum sollten Sie das Rad neu erfinden, wenn es schon fertige R-Pakete gibt, die Ihre Bedürfnisse bedienen? Hier lernen Sie sie kennen.
R in a Nutshell: A Desktop Quick Reference
by Joseph AdlerIf you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
R kompakt: Der schnelle Einstieg in die Datenanalyse
by Daniel WollschlägerDieses Buch bietet eine kompakte Einführung in die Datenauswertung mit der freien Statistikumgebung R. Ziel ist es dabei, einen Überblick über die Funktionalität von R zu liefern und einen schnellen Einstieg in die deskriptive Datenauswertung sowie in die Umsetzung der wichtigsten statistischen Tests zu ermöglichen. Zudem deckt das Buch die vielfältigen Möglichkeiten ab, Diagramme zu erstellen, Daten mit anderen Programmen auszutauschen und R durch Zusatzpakete zu erweitern. Das Buch ist damit für Leser geeignet, die R kennenlernen und rasch in konkreten Aufgabenstellungen einsetzen möchten.Für die 3. Auflage wurde das Buch grundlegend überarbeitet und auf Neuerungen der R Version 4.1.0 sowie der aktuellen Landschaft der Zusatzpakete abgestimmt. Mit einer stärkeren Ausrichtung auf Data Science Anwendungen stellt das Buch nun ausführlich die Pakete dplyr zur Datenaufbereitung und ggplot2 für Diagramme vor. Darüber hinaus enthält das Buch eine Darstellung von dynamischen R Markdown Dokumenten zur Unterstützung reproduzierbarer Auswertungen.
R-Calculus, V: Description Logics (Perspectives in Formal Induction, Revision and Evolution)
by Wei Li Yuefei SuiThis book series consists of two parts, decidable description logics and undecidable description logics. It gives the R-calculi for description logics. This book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners in the field of logic.
R-Calculus, VI: Finite Injury Priority Method (Perspectives in Formal Induction, Revision and Evolution)
by Wei Li Yuefei SuiThis sixth volume of the book series applies finite injury priority method to R-calculi and obtain (in)completeness theorem for binary-valued, Post three-valued, B2^2-valued and L4-valued first-order logics, and extend the method to infinite injury priority method and 0"-method for default logic to produce pseudo-extensions of a default theory, corresponding to different R-calculi. Finite injury priority method and tree constructions are discussed in this book. This book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners in the field of logic.
R-ticulate: A Beginner's Guide to Data Analysis for Natural Scientists
by Martin Bader Sebastian LeuzingerAn accessible learning resource that develops data analysis skills for natural science students in an efficient style using the R programming language R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists is a compact, example-based, and user-friendly statistics textbook without unnecessary frills, but instead filled with engaging, relatable examples, practical tips, online exercises, resources, and references to extensions, all on a level that follows contemporary curricula taught in large parts of the world. The content structure is unique in the sense that statistical skills are introduced at the same time as software (programming) skills in R. This is by far the best way of teaching from the authors’ experience. Readers of this introductory text will find: Explanations of statistical concepts in simple, easy-to-understand language A variety of approaches to problem solving using both base R and tidyverse Boxes dedicated to specific topics and margin text that summarizes key points A clearly outlined schedule organized into 12 chapters corresponding to the 12 semester weeks of most universities While at its core a traditional printed book, R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists comes with a wealth of online teaching material, making it an ideal and efficient reference for students who wish to gain a thorough understanding of the subject, as well as for instructors teaching related courses.
R. Edward Freeman’s Selected Works on Stakeholder Theory and Business Ethics (Issues in Business Ethics #53)
by R. Edward Freeman Sergiy D. DmytriyevEd Freeman’s influential ideas on stakeholder theory, business ethics, humanities, and capitalism became foundational in the management field and turned around the mainstream thinking about business. Stakeholder theory developed by Freeman and others posits that business is not as much about profits, but rather about creating value for its stakeholders, including employees, customers, communities, financiers, and suppliers. The relationship between a company and its stakeholders is the essence of business and should be of utmost attention to its managers. Managers should avoid resorting to trade-offs by prioritizing one stakeholder group (e.g., shareholders) over the others and strive to run their companies in the interests of all stakeholders. The idea of pursuing the interests of all stakeholders became revolutionary in management and went far beyond the management field, expanding to Law, Health Care, Education, Public Policy and Administration, and Environmental Policy. This book is a collection of Ed Freeman’s most influential and important works on stakeholder theory as well as business ethics, humanities, and capitalism.
RC4 Stream Cipher and Its Variants
by Goutam Paul Subhamoy MaitraRC4 Stream Cipher and Its Variants is the first book to fully cover the popular software stream cipher RC4. With extensive expertise in stream cipher cryptanalysis and RC4 research, the authors focus on the analysis and design issues of RC4. They also explore variants of RC4 and the eSTREAM finalist HC-128.After an introduction to the vast field of
REDUCE for Physicists
by N MacDonaldThe use of computer algebra systems in science and engineering has grown rapidly as more people realize their potential to solve tedious and extensive mathematical problems. REDUCE for Physicists provides a comprehensive introduction to one of the most widely available and simple to use computer algebra systems, focusing primarily on the needs of physicists. As a means of performing symbolic computation, REDUCE reduces tedious manual algebraic calculations and the dangers of casual errors. Each chapter introduces some aspects of REDUCE and illustrates them with applications from various branches of physics including mechanics, dynamics, dimensional analysis, quantum mechanics, and plasma physics. Emphasizing hands-on work with REDUCE to tackle real physical problems, the book includes exercises to test understanding throughout. Students and researchers in the physical sciences and engineering using REDUCE for the first time will find this book an invaluable aid to learning.
RNA Bioinformatics
by Ernesto PicardiThis volume provides an overview of RNA bioinformatics methodologies, including basic strategies to predict secondary and tertiary structures, and novel algorithms based on massive RNA sequencing. Interest in RNA bioinformatics has rapidly increased thanks to the recent high-throughput sequencing technologies allowing scientists to investigate complete transcriptomes at single nucleotide resolution. Adopting advanced computational technics, scientists are now able to conduct more in-depth studies and present them to you in this book. Written in the highly successful Methods of Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and equipment, step-by-step, readily reproducible bioinformatics protocols, and key tips to avoid known pitfalls. Authoritative and practical, RNA Bioinformatics seeks to aid scientists in the further study of bioinformatics and computational biology of RNA.
RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods
by Jan Gorodkin Walter L. RuzzoThe existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes. However, a long series of striking discoveries, from RNA's ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere. However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In RNA Sequence, Structure, Function: Computational and Bioinformatic Methods, expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in more detailed aspects of the algorithms. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results. Thorough and intuitive, RNA Sequence, Structure, Function: Computational and Bioinformatic Methods aids scientists in continuing to study key methods and principles of RNA bioinformatics.
RNA-seq Data Analysis: A Practical Approach (Chapman & Hall/CRC Computational Biology Series)
by Eija Korpelainen Jarno Tuimala Panu Somervuo Mikael Huss Garry WongThe State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le
ROC Analysis for Classification and Prediction in Practice
by Christos NakasThis book presents a unified and up-to-date introduction to ROC methodologies, covering both diagnosis (classification) and prediction. The emphasis is on the conceptual underpinning of ROC analysis and the practical implementation in diverse scientific fields. A plethora of examples accompany the methodologic discussion using standard statistical software such as R and STATA. The book arrives after two decades of intensive growth in both the methods and the applications of ROC analysis and presents a new synthesis. The authors provide a contemporary, integrated exposition of ROC methodology for both classification and prediction and include material on multiple-class ROC. This book avoids lengthy technical exposition and provides code and datasets in each chapter. ROC Analysis for Classification and Prediction in Practice is intended for researchers and graduate students, but will also be useful for those that use ROC analysis in diverse disciplines such as diagnostic medicine, bioinformatics, medical physics, and perception psychology.
ROC Curves for Continuous Data (ISSN #111)
by David J. Hand Wojtek J. KrzanowskiSince ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.The fundamenta
RSA and Public-Key Cryptography
by Richard A. MollinAlthough much literature exists on the subject of RSA and public-key cryptography, until now there has been no single source that reveals recent developments in the area at an accessible level. Acclaimed author Richard A. Mollin brings together all of the relevant information available on public-key cryptography (PKC), from RSA to the latest applic
RStudio for R Statistical Computing Cookbook
by Andrea CirilloOver 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature About This Book * 54 useful and practical tasks to improve working systems * Includes optimizing performance and reliability or uptime, reporting, system management tools, interfacing to standard data ports, and so on * Offers 10-15 real-life, practical improvements for each user type Who This Book Is For This book is targeted at R statisticians, data scientists, and R programmers. Readers with R experience who are looking to take the plunge into statistical computing will find this Cookbook particularly indispensable. What You Will Learn * Familiarize yourself with the latest advanced R console features * Create advanced and interactive graphics * Manage your R project and project files effectively * Perform reproducible statistical analyses in your R projects * Use RStudio to design predictive models for a specific domain-based application * Use RStudio to effectively communicate your analyses results and even publish them to a blog * Put yourself on the frontiers of data science and data monetization in R with all the tools that are needed to effectively communicate your results and even transform your work into a data product In Detail The requirement of handling complex datasets, performing unprecedented statistical analysis, and providing real-time visualizations to businesses has concerned statisticians and analysts across the globe. RStudio is a useful and powerful tool for statistical analysis that harnesses the power of R for computational statistics, visualization, and data science, in an integrated development environment. This book is a collection of recipes that will help you learn and understand RStudio features so that you can effectively perform statistical analysis and reporting, code editing, and R development. The first few chapters will teach you how to set up your own data analysis project in RStudio, acquire data from different data sources, and manipulate and clean data for analysis and visualization purposes. You'll get hands-on with various data visualization methods using ggplot2, and you will create interactive and multidimensional visualizations with D3.js. Additional recipes will help you optimize your code; implement various statistical models to manage large datasets; perform text analysis and predictive analysis; and master time series analysis, machine learning, forecasting; and so on. In the final few chapters, you'll learn how to create reports from your analytical application with the full range of static and dynamic reporting tools that are available in RStudio so that you can effectively communicate results and even transform them into interactive web applications. Style and approach RStudio is an open source Integrated Development Environment (IDE) for the R platform. The R programming language is used for statistical computing and graphics, which RStudio facilitates and enhances through its integrated environment. This Cookbook will help you learn to write better R code using the advanced features of the R programming language using RStudio. Readers will learn advanced R techniques to compute the language and control object evaluation within R functions. Some of the contents are: * Accessing an API with R * Substituting missing values by interpolation * Performing data filtering activities * R Statistical implementation for Geospatial data * Developing shiny add-ins to expand RStudio functionalities * Using GitHub with RStudio * Modelling a recommendation engine with R * Using R Markdown for static and dynamic reporting * Curating a blog through RStudio * Advanced statistical modelling with R and RStudio
Rabi N. Bhattacharya
by Manfred Denker Edward C. WaymireThis volume presents some of the most influential papers published by Rabi N. Bhattacharya, along with commentaries from international experts, demonstrating his knowledge, insight, and influence in the field of probability and its applications. For more than three decades, Bhattacharya has made significant contributions in areas ranging from theoretical statistics via analytical probability theory, Markov processes, and random dynamics to applied topics in statistics, economics, and geophysics. Selected reprints of Bhattacharya's papers are divided into three sections: Modes of Approximation, Large Times for Markov Processes, and Stochastic Foundations in Applied Sciences. The accompanying articles by the contributing authors not only help to position his work in the context of other achievements, but also provide a unique assessment of the state of their individual fields, both historically and for the next generation of researchers. Rabi N. Bhattacharya: Selected Papers will be a valuable resource for young researchers entering the diverse areas of study to which Bhattacharya has contributed. Established researchers will also appreciate this work as an account of both past and present developments and challenges for the future.