在哪里可以找到具有各种实现方式的有用的R教程? [英] Where can I find useful R tutorials with various implementations?

问题描述

我正在使用> R 语言以及R网站确实提供了很多信息.但是，我希望看到更多使用R的示例和实现，它们可以帮助我更快地发展知识.有什么建议吗?

I'm using R language and the manuals on the R site are really informative. However, I'd like to see some more examples and implementations with R which can help me develop my knowledge faster. Any suggestions?

推荐答案

我会提到一些我认为是很好的资源，但是我并没有在SO上提到它们.它们都是免费的，并且可以在Web上免费获得(提供链接).

I'll mention a few that i think are excellent resources but that i haven't seen mentioned on SO. They are all free and freely available on the Web (links supplied).

数据分析示例 您可以按主要类别浏览UCLA统计部单个示例的集合(例如计数模型"，多元分析"，幂分析")，然后在任何这些标题下下载带有完整R代码的示例(例如，在计数模型"下是泊松回归"，负二项式回归"等等.

Data Analysis Examples A collection of individual examples from the UCLA Statistics Dept. which you can browse by major category (e.g., "Count Models", "Multivariate Analysis", "Power Analysis") then download examples with complete R code under any of these rubrics (e.g., under "Count Models" are "Poisson Regression", "Negative Binomial Regression", and so on).

Verzani:SimpleR:使用R进行介绍统计信息 ，略多于100页，非常出色.易于遵循，但非常密集.已经有几年了，在本文中我仍然只发现了一个不推荐使用的功能.这是一个崭新的R用户的资源；它也恰好是出色的统计资料复习.本文可能包含20多个针对基础统计(例如，假设检验，线性回归，简单模拟和描述性统计)的示例(带有R代码和解释).

Verzani: SimpleR: Using R for Introductory Statistics A little over 100 pages, and just outstanding. It's easy to follow but very dense. It is a few years old, still i've only found one deprecated function in this text. This is a resource for a brand new R user; it also happens to be an excellent statistics refresher. This text probably contains 20+ examples (with R code and explanation) directed to fundamental statistics (e.g., hypothesis testing, linear regression, simple simulation, and descriptive statistics).

具有R的统计信息 (Vincent Zoonekynd)，您可以在线阅读或将其打印为pdf.印刷超过1000页.作者显然是通过阅读他所讨论的各种功能的源代码而获得了大量信息的-在这里有很多信息，我在任何其他来源中都找不到.此资源包含有关图形，基本统计信息，回归，时间序列的大部分内容-均带有小示例(R代码+说明).最后的三个部分包含了最具有示范性的代码-关于财务(这似乎是作者的专业领域)，遗传学和图像分析的非常详尽的应用程序部分.

Statistics with R (Vincent Zoonekynd) You can read it online or print it as a pdf. Printed it's well over 1000 pages. The author obviously got a lot of the information by reading the source code for the various functions he discusses--a lot of the information here, i haven't found in any other source. This resource contains large sections on Graphics, Basic Statistics, Regression, Time Series--all w/ small examples (R code + explanation). The final three sections contain the most exemplary code--very thorough application sections on Finance (which seems to be the author's professional field), Genetics, and Image Analysis.

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