Extending R
Extending R

Author: John M. Chambers

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 420

ISBN-13: 1315349876

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Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R. A 2017 Choice Outstanding Academic Title

Linear Models with R
Linear Models with R

Author: Julian J. Faraway

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 284

ISBN-13: 1439887349

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A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models

Extending Power BI with Python and R
Extending Power BI with Python and R

Author: Luca Zavarella

Publisher: Packt Publishing Ltd

Published: 2021-11-26

Total Pages: 559

ISBN-13: 1801076677

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Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R Key FeaturesGet the most out of Python and R with Power BI by implementing non-trivial codeLeverage the toolset of Python and R chunks to inject scripts into your Power BI dashboardsImplement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BIBook Description Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you'll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R. What you will learnDiscover best practices for using Python and R in Power BI productsUse Python and R to perform complex data manipulations in Power BIApply data anonymization and data pseudonymization in Power BILog data and load large datasets in Power BI using Python and REnrich your Power BI dashboards using external APIs and machine learning modelsExtract insights from your data using linear optimization and other algorithmsHandle outliers and missing values for multivariate and time-series dataCreate any visualization, as complex as you want, using R scriptsWho this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.

Advanced R
Advanced R

Author: Hadley Wickham

Publisher: CRC Press

Published: 2015-09-15

Total Pages: 669

ISBN-13: 1498759807

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An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.

Language Arts
Language Arts

Author: Marjorie R. Hancock

Publisher: Prentice Hall

Published: 2007

Total Pages: 552

ISBN-13:

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CD-ROM contains a database of information on thousands of children's literature titles, which helps you find titles for a lesson, unit, or read-aloud, or for one specific reader. User can search by topic, author, genre, or title. Software must be installed from CD.

R for Data Science
R for Data Science

Author: Hadley Wickham

Publisher: "O'Reilly Media, Inc."

Published: 2016-12-12

Total Pages: 521

ISBN-13: 1491910364

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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Real Analysis
Real Analysis

Author: Peter A. Loeb

Publisher: Birkhäuser

Published: 2016-05-05

Total Pages: 278

ISBN-13: 3319307444

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This textbook is designed for a year-long course in real analysis taken by beginning graduate and advanced undergraduate students in mathematics and other areas such as statistics, engineering, and economics. Written by one of the leading scholars in the field, it elegantly explores the core concepts in real analysis and introduces new, accessible methods for both students and instructors. The first half of the book develops both Lebesgue measure and, with essentially no additional work for the student, general Borel measures for the real line. Notation indicates when a result holds only for Lebesgue measure. Differentiation and absolute continuity are presented using a local maximal function, resulting in an exposition that is both simpler and more general than the traditional approach. The second half deals with general measures and functional analysis, including Hilbert spaces, Fourier series, and the Riesz representation theorem for positive linear functionals on continuous functions with compact support. To correctly discuss weak limits of measures, one needs the notion of a topological space rather than just a metric space, so general topology is introduced in terms of a base of neighborhoods at a point. The development of results then proceeds in parallel with results for metric spaces, where the base is generated by balls centered at a point. The text concludes with appendices on covering theorems for higher dimensions and a short introduction to nonstandard analysis including important applications to probability theory and mathematical economics.

Extensions of Rings and Modules
Extensions of Rings and Modules

Author: Gary F. Birkenmeier

Publisher: Springer Science & Business Media

Published: 2013-07-19

Total Pages: 442

ISBN-13: 0387927166

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The "extensions" of rings and modules have yet to be explored in detail in a research monograph. This book presents state of the art research and also stimulating new and further research. Broken into three parts, Part I begins with basic notions, terminology, definitions and a description of the classes of rings and modules. Part II considers the transference of conditions between a base ring or module and its extensions. And Part III utilizes the concept of a minimal essental extension with respect to a specific class (a hull). Mathematical interdisciplinary applications appear throughout. Major applications of the ring and module theory to Functional Analysis, especially C*-algebras, appear in Part III, make this book of interest to Algebra and Functional Analysis researchers. Notes and exercises at the end of every chapter, and open problems at the end of all three parts, lend this as an ideal textbook for graduate or advanced undergradate students.

AI and Cognitive Science ’92
AI and Cognitive Science ’92

Author: Kevin Ryan

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 354

ISBN-13: 1447132076

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The annual Irish Conferences on Artificial Intelligence and Cognitive Science have become the major forum in Ireland for the discussion of various aspects of artificial intelligence. Their aim is to provide a forum where researchers can present their current work, and where industrial and commercial users can relate this work to their own practical needs and experiences. Although the emphasis of the conferences is on Irish research, there are also important contributions from Europe, Australia, Canada, and the USA. This volume is based on the proceedings of the Fifth Irish Conference on Artificial Intelligence and Cognitive Science (AICS'92), which was held at the University of Limerick, Ireland, from 10-11 September 1992. The conference was divided into 6 sessions, covering knowledge representation, cognitive foundations, natural language 1 and 2, learning and expert systems, and nov§ el aspects of artificial intelligence and cognitive science. Because of the high number of papers submitted to the conference, a poster session was run in addition to the plenary sessions. Each paper presented at the poster session is represented in this volume by a four page abstract. Among the specific topics covered in this volume are: a model-based theory of conceptual combination; the nature and development of reasoning strategies; word recognition as a parsing problem; a knowledge-based autonomous vehicle system for emergency management support; the construction and use of scope neutral discourse entities; computer-based iconic communication; and exceptions in multiple inheritance systems. AI and Cognitive Science '92 provides a comprehensive record of current research into this important field. It will be of interest to researchers, lecturers and postgraduate students in a variety of disciplines related to artificial intelligence and cognitive science.

R Cookbook
R Cookbook

Author: Paul Teetor

Publisher: O'Reilly Media

Published: 2011-03-03

Total Pages: 436

ISBN-13: 144930737X

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With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author