P228

现代统计图形 r语言 文档

现代统计图形 r语言

2018-01-04   3   0
P39

r语言的绘图功能及应用案例 文档

2017-03-09   2   0
P5

  r语言作业 文档

2017-01-05   1   0
P8

google 的 r 语言编码风格指南 文档

R 语言是一门主要用于统计计算和绘图的高级编程语言. 这份 R 语言编码风格指南旨在让我们的R 代码更容易阅读、分享和检查. 以下规则系与 Google 的 R 用户群体协同设计而成

2016-12-12   2   0
P193

the art of r programming 文档

This book is for those who wish to write code in R, as opposed to those who use R mainly for a sequence of separate, discrete statistical operations, plotting a histogram here, performing a regression analysis there.The reader’s level of programming background may range from professional to novice to “took a programming course in college,” but the key is that the reader wishes to write R code. Typical examples of our intended audience might be:

2016-11-30   3238   0
P8

  r语言 常用函数 文档

2016-09-23   1   0
P66

医学统计学之r实现 文档

本文所引用数据的版权,归《医学统计学及 SAS 应用》原作者所有。本文只探讨使用 R 实 现的可能性,并且仅对本文中 R 语言代码享有相关权利。此处还想特别感谢该书的编者之 一,上海交通大学医学院生物统计学教研室的王筱金老师,正是得益于她的用心教学,本文 作者才学会基本的统计学知识,也因此才有这份笔记。

2016-04-08   5671   0
P54

Introductory Statistics with R_chapter_3-5 文档

R is an Open Source implementation of the well-known S language. It works on multiple computing platforms and can be freely downloaded. R is thus ideally suited for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets.

2016-03-04   2   0
P126

学习RStudio用于R统计计算 文档

学习RStudio用于R统计计算。Learn to effectively perform R development, statistical analysis, and reporting with the most popular R IDE

2016-02-29   3016   0
P209

R快速语法参考 文档

R is a programming language that provides the user with powerful data and graphical analysis options. R is both flexible and broad. From tasks as simple as adding two numbers to tasks as complex as fitting an ARIMA model, R is capable of crunching the numbers. <br> The purpose of R Quick Syntax Reference is to provide the reader with the basic syntax of R. Often an R user gets stuck if, for example, a mode is incorrect or a logical test does not work. Because the full spectrum of R packages uses the same fairly simple syntax, R Quick Syntax Reference provides the reader with the necessary information to get unstuck and run and create all R functions and code.

2016-02-15   3   0
P110

Web Application Development with R Using Shiny 文档

Harness the graphical and statistical power of R and rapidly develop interactive user interfaces using the superb Shiny package

2016-02-14   2   0
P441

An Introduction to Statistical Learning with Applications in R 文档

1,统计学习的入门书,通俗易懂,号称是ESL的入门版,全书没有太多数学推导,适合学工程的人不适合学统计的人读。2,监督学习占了大部分篇幅,我觉得这本书最好的部分就是模型的讨论都围绕variance和bias的trade-off展开,还有就是对模型的整体性能,以及参数的经验取值都给出了非常详细的介绍。 An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

2016-02-05   3   0
P0

数据挖掘与R语言(英文版) 文档

本书利用大量给出必要步骤、代码和数据的具体案例,详细描述了数据挖掘的主要过程和技术,广泛涵盖数据大小、数据类型、分析目标、分析工具等方面的各种具有挑战性的问题。 本书的支持网站给出了案例研究的所有代码、数据集以及R函数包。 通过仔细选择的案例涵盖了主要的数据挖掘技术。   给出的代码和方法可以方便地复制或者改编后应用于自己的问题。   不要求读者具有R、数据挖掘或统计技术的基础知识。   包含R和MySQL基础知识的简介。   提供了对数据挖掘技术的特性、缺点和分析目标的基本理解。

2016-02-02   1   0
P296

使用R语言进行数据管理,统计分析和图形化 文档

Using R for Data Management, Statistical Analysis, and Graphics。Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation and vast number of add-on packages. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods, and the creation of graphics.

2016-02-02   4   0
P0

时间序列分析及其在R上的应用 文档

时间序列分析及其在R上的应用。 Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using non-trivial data illustrate solutions to problems such as evaluating pain perception experiments using magnetic resonance imaging or monitoring a nuclear test ban treaty. The book is designed to be useful as a text for graduate level students in the physical, biological and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. Material from the earlier 1988 Prentice-Hall text Applied Statistical Time Series Analysis has been updated by adding modern developments involving categorical time sries analysis and the spectral envelope, multivariate spectral methods, long memory series, nonlinear models, longitudinal data analysis。

2016-02-02   2   0
P404

R语言编程艺术(英文版) 文档

这本书涵盖了R语言编程的诸多方面,尤其在面向对象编程、程序调试、提升程序运行速度以及并行计算等方面,填补了同类图书的空白。关于程序调试的章节更是作者多年经验的总结。不管是初学者还是有一定编程经验的读者,阅读这本书都会有所收获。R语言是世界上最流行的用于数据处理和统计分析的脚本语言。考古学家用它来跟踪古代文明的传播,医药公司用它来探索哪种药物更安全、更有效,精算师用它评估金融风险以保证市场的平稳运行。总之,在大数据时代,统计数据、分析数据都离不开计算机软件的支持,在这方面R语言尤其出色。 本书将带领你踏上R语言软件开发之旅,从最基本的数据类型和数据结构开始,到闭包、递归和匿名函数等高级主题,由浅入深,讲解细腻,读者完全不需要统计学的知识,甚至不需要编程基础。而书中提到的很多高级编程技巧,都是作者多年编程经验的总结,对有经验的开发者也大有裨益。本书精选了44个扩展案例,这些案例都源自于作者亲身参与过的咨询项目,都是与数据分析相关的,生动展示了R语言在统计学中的高效应用。

2016-02-02   3   0
P72

R语言入门 文档

R是一套由数据操作、计算和图形展示功能整合而成的套件。包括: ² 有效的数据存储和处理功能, ² 一套完整的数组(特别是矩阵)计算操作符, ² 拥有完整体系的数据分析工具, ² 为数据分析和显示提供的强大图形功能, ² 一套(源自S语言)完善、简单、有效的编程语言(包括条件、循环、自 定义函数、输入输出功能)。 在这里使用"环境"(environment)是为了说明R的定位是一个完善、统一的系 统,而非其他数据分析软件那样作为一个专门、不灵活的附属工具。 R很适合被用于发展中的新方法所进行的交互式数据分析。由于R是一个动 态的环境,所以新发布的版本并不总是与之前发布的版本完全兼容。某些用户 欢迎这些变化因为新技术和新方法的所带来的好处;有些则会担心旧的代码不 再可用。尽管R试图成为一种真正的编程语言,但是大家不要认为一个由R编写 的程序可以长命百岁。

2016-02-02   3   0
P72

R语言入门教程 文档

R是一套由数据操作、计算和图形展示功能整合而成的套件。包括: ² 有效的数据存储和处理功能, ² 一套完整的数组(特别是矩阵)计算操作符, ² 拥有完整体系的数据分析工具, ² 为数据分析和显示提供的强大图形功能, ² 一套(源自S语言)完善、简单、有效的编程语言(包括条件、循环、自 定义函数、输入输出功能)。 在这里使用"环境"(environment)是为了说明R的定位是一个完善、统一的系 统,而非其他数据分析软件那样作为一个专门、不灵活的附属工具。 R很适合被用于发展中的新方法所进行的交互式数据分析。由于R是一个动 态的环境,所以新发布的版本并不总是与之前发布的版本完全兼容。某些用户 欢迎这些变化因为新技术和新方法的所带来的好处;有些则会担心旧的代码不 再可用。尽管R试图成为一种真正的编程语言,但是大家不要认为一个由R编写 的程序可以长命百岁。

2015-12-25   6   0
P628

R语言实战 (R in Action)英文版第二版 文档

数据时代已经到来,但数据分析、数据挖掘人才却十分短缺。由于“大数据”对每个领域的决定性影响, 相对于经验和直觉,在商业、经济及其他领域中基于数据和分析去发现问题并作出科学、客观的决策越来越重要。开源软件R是世界上最流行的数据分析、统计计算及制图语言,几乎能够完成任何数据处理任务,可安装并运行于所有主流平台,为我们提供了成千上万的专业模块和实用工具,是从大数据中获取有用信息的绝佳工具。  本书从解决实际问题入手,尽量跳脱统计学的理论阐述来讨论R语言及其应用,讲解清晰透澈,极具实用性。作者不仅高度概括了R语言的强大功能、展示了各种实用的统计示例,而且对于难以用传统方法分析的凌乱、不完整和非正态的数据也给出了完备的处理方法。通读本书,你将全面掌握使用R语言进行数据分析、数据挖掘的技巧,并领略大量探索和展示数据的图形功能,从而更加高效地进行分析与沟通。想要成为倍受高科技企业追捧的、炙手可热的数据分析师吗?想要科学分析数据并正确决策吗?不妨从本书开始,挑战大数据,用R开始炫酷的数据统计与分析吧!

2015-12-20   8   0
P53

R & Bioconductor Manual 文档

This R tutorial provides a condensed introduction into the usage of the R environment and its utilities for general data analysis and clustering. It also introduces a subset of packages from the BioConductor project. The included packages are a 'personal selection' of the author of this manual that does not reflect the full utility specturm of the R/BioConductor projects. Many packages were chosen, because the author uses them often for his own teaching and research. To obtain a broad overview of available R packages, it is strongly recommended to consult the official BioConductor and R project sites. Due to the rapid development of most packages, it is also important to be aware that this manual will often not be fully up-to-date. Because of this and many other reasons, it is absolutley critical to use the original documentation of each package (PDF manual or vignette) as primary source of documentation. Users are welcome to send suggestions for improving this manual directly to its author.

2015-12-13   0   0
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