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Impatient R

Impatient R
Translations français: Translated by Kate Bondareva. Serbo-Croatian: Translated by Jovana Milutinovich from Geeks Education. Preface This is a tutorial (previously known as “Some hints for the R beginner”) for beginning to learn the R programming language. It is a tree of pages — move through the pages in whatever way best suits your style of learning. You are probably impatient to learn R — most people are. This page has several sections, they can be put into the four categories: General, Objects, Actions, Help. General Introduction Blank screen syndrome Misconceptions because of a previous language Helpful computer environments R vocabulary Epilogue Objects Key objects Reading data into R Seeing objects Saving objects Magic functions, magic objects Some file types Packages Actions What happens at R startup Key actions Errors and such Graphics Vectorization Make mistakes on purpose

Introdução ao Ambiente Estatístico R Paulo Justiniano Ribeiro Junior Última atualização: 29 de maio de 2011 Estas notas foram inicialmente escritas para um curso de introdução ao sistema estatístico R ministrado para profissionais da EMBRAPA em Brasília, 30/05 a 03/06 de 2005. Desde sua versão inicial o material tem sido constantemente modificado com a expansão, correção e inclusão de tópicos. O objetivo é ilustrar aspectos básicos do sistema com ênfase na compreensão de aspectos básicos da linguagem, a estrutura e a forma de operar o programa. Na maior parte do texto assume-se apenas familiaridade com conceitos e métodos básicos de estatística. O texto começa com uma Seção que tem como objetivo "experimentar o R", o que permite ter uma idéia de seus recursos e a forma de trabalhar com este programa. Para utilizar o R siga os seguintes passos: inicie o R em seu computador; voce verá uma janela de comandos com o símbolo >; que é chamado de prompt do R, indicando que o programa está pronto para receber comandos;

R Programming Language | ProgrammingR TCL/TK Command Reference Guide Binding scripts can contains % substitution codes to insert details about the event. When executed, a new script is generated which replaces the substitution codes with an properly formatted list containing the specified information from the current event. Invalid substitutions are undefined. For some of the above substitutions, the possible replacement strings are: 3.2 Button Widget Button Widget Options Standard See Common Options and Resources in Options and Resources for full details. Button Widget Specific See Coordinates in General Tk Widget Information for screen unit options. Button Widget Commands Default Button Widget Bindings Active or normal button default bindings: 3.3 Canvas Widget Canvas Options Canvas Specific See Coordinates in Options and Resources for screen unit options. Item IDs and Tags Each item in a canvas widget has an unique id and one or more tags. Indicies or Character Positions: Canvas Commands Canvas Item Standard Options Canvas Item Commands 3.4 Checkbutton Definitions Mac:

The Endeavour | John D. Cook I help people make decisions in the face of uncertainty. Sounds interesting. I’m a data scientist. Not sure what that means, but it sounds cool. I study machine learning. Hmm. I’m into big data. Even though each of these descriptions makes a different impression, they’re all essentially the same thing. There are distinctions. “Decision-making under uncertainty” emphasizes that you never have complete data, and yet you need to make decisions anyway. “Data science” stresses that there is more to the process of making inferences than what falls under the traditional heading of “statistics.” Despite the hype around the term data science, it’s growing on me. Machine learning, like decision theory, emphasizes the ultimate goal of doing something with data rather than creating an accurate model of the process that generates the data. “Big data” is a big can of worms. Bayesian statistics is much older than what is now sometimes called “classical” statistics.

Cookbook for R » Cookbook for R Welcome to the Tclers Wiki! The R programming language for programmers coming from other programming languages IntroductionAssignment and underscoreVariable name gotchasVectorsSequencesTypesBoolean operatorsListsMatricesMissing values and NaNsCommentsFunctionsScopeMisc.Other resources Ukrainian translation Other languages: Powered by Translate Introduction I have written software professionally in perhaps a dozen programming languages, and the hardest language for me to learn has been R. R is more than a programming language. This document is a work in progress. Assignment and underscore The assignment operator in R is <- as in e <- m*c^2. It is also possible, though uncommon, to reverse the arrow and put the receiving variable on the right, as in m*c^2 -> e. It is sometimes possible to use = for assignment, though I don't understand when this is and is not allowed. However, when supplying default function arguments or calling functions with named arguments, you must use the = operator and cannot use the arrow. At some time in the past R, or its ancestor S, used underscore as assignment. Vectors Sequences

R Beginner's Guide and R Bloggers Updates 1/1/2011 Update: Tal Galili wrote an article that revisits the first year of R-Bloggers and this post was listed as one of the top 14. Therefore, I decided to make a small update to each section. I start by describing the initial series of tutorials that I wrote. A few more have been added since and even more planned in the upcoming year. As always, an up to date listing of my articles can be found on the R Tutorial Series blog. Since October 2009, I have written 13 articles [many more now, of course] for the R Tutorial Series blog. Introduction to R Descriptive Statistics Summary and Descriptive Statistics Data Visualization Scatterplots Correlation Zero-Order Correlations Regression I also have two additional R-related items to update you on. 1/1/2011 Update: I originally reported that 50 blogs composed the R Bloggers network. R Tutorial Series on R Bloggers R Bloggers ( is a website that aggregates over 50 different blogs that focus on R. R Beginner's Guide

R TclTk coding examples R TclTk coding examples If you want to use the tcltk package in R (contributed by Peter Dalgaard), you will find here useful hints. This collection of R tcltk tips & tricks was initially compiled by James Wettenhall. Installing Tcl/Tk for R Make sure you check the "Support Files for Package tcltk" when you install R for Windows. For other platforms, you have to make sure Tcl/Tk 8.4 is installed. Basic techniques Simple toplevel window with an OK buttonMessage boxesFile open/save dialogsPull-down menus and popup menusA modal dialog boxSimple non-modal dialog with OK and Cancel buttons and a title Basic widgets Making a button to trigger a function callAdding and changing text labelsCheckboxesRadio buttonsEdit boxesList boxes Additional widgets Advanced tcltk coding Useful links Other sources of R tcltk help/examples

Data Sorcery with Clojure R Programming - Manuals R Basics The R & BioConductor manual provides a general introduction to the usage of the R environment and its basic command syntax. Code Editors for R Several excellent code editors are available that provide functionalities like R syntax highlighting, auto code indenting and utilities to send code/functions to the R console. Programming in R using Vim or Emacs Programming in R using RStudio Integrating R with Vim and Tmux Users interested in integrating R with vim and tmux may want to consult the Vim-R-Tmux configuration page. Finding Help Reference list on R programming (selection)R Programming for Bioinformatics, by Robert GentlemanAdvanced R, by Hadley WickhamS Programming, by W. Control Structures Conditional Executions Comparison Operators equal: ==not equal: ! Logical Operators If Statements If statements operate on length-one logical vectors. Syntax if(cond1=true) { cmd1 } else { cmd2 } Example if(1==0) { print(1) } else { print(2) } [1] 2 Avoid inserting newlines between '} else'. Loops Syntax

R TclTk Examples R TclTk Examples The following examples have been compiled by James Wettenhall in Windows to help people to learn how to use the tcltk package in R, contributed by Peter Dalgaard. If you are having trouble installing R TclTk in Windows, click here and also read Brian Ripley's R for Windows FAQ in the Help pull-down menu of RGui. Please follow the final link at the bottom of this page to find some very useful external sources of R TclTk examples and documentation.

R for Psych Research This is one page of a series of tutorials for using R in psychological research. Much of material has also covered been covered in number of short courses or in a set of tutorials for specific problems. This particular page is an update of a previous guide to R which is being converted to HTML5 to be more readable. (For a very abbreviated form of this guide meant to help students do basic data analysis in a personality research course, see a very short guide. There are many possible statistical programs that can be used in psychological research. It has been claimed that "The statistical programming language and computing environment S has become the de-facto standard among statisticians. The R project, based upon the S and S+ stats packages, has developed an extremely powerful set of "packages" that operate within one program. Although many run R as a language and programming environment, there are Graphical User Interfaces (GUIs) available for PCs, Linux and Macs. Back to Top entering ?

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