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* asdf | |
```{r} | |
'asdf' | |
``` |
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#!/bin/bash | |
bibtexstylefile=apalike | |
bibtexdatabase=$BIB | |
pdfdirectory=$BIBDIR | |
pdfprogram=evince | |
pandocoutputformat=plain | |
# returntask | |
# bibtex : return bibtex record (default) | |
# format : return |
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This document is just a test of RPubs platform for publishing R Markdown. I'll use the `survey` dataset from the `MASS` package to explore a few features. | |
```{r get_data, message=FALSE} | |
library(MASS) | |
library(psych) | |
library(Hmisc) | |
library(xtable) | |
data(survey) | |
``` |
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" | |
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> | |
<!-- saved from url=(0014)about:internet --> | |
<html> | |
<head> | |
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
<title></title> | |
<base target="_blank"/> |
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" | |
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> | |
<!-- saved from url=(0014)about:internet --> | |
<html> | |
<head> | |
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
<title></title> |
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`r opts_chunk$set(cache=TRUE)` | |
This is a quick set of analyses of the California Test Score dataset. The post was produced using R Markdown in RStudio 0.96. The main purpose of this post is to provide a case study of using R Markdown to prepare a quick reproducible report. It provides examples of using plots, output, in-line R code, and markdown. The post is designed to be read along side the R Markdown source code, which is available as a gist on github. | |
<!-- more --> | |
### Preliminaries | |
* This post builds on my earlier post which provided a guide for [Getting Started with R Markdown, knitr, and RStudio 0.96](jeromyanglim.blogspot.com/2012/05/getting-started-with-r-markdown-knitr.html) | |
* The dataset analysed comes from the `AER` package which is an accompaniment to the book [Applied Econometrics with R](http://www.amazon.com/Applied-Econometrics-R-Use/dp/0387773169) written by [Christian Kleiber](http://wwz.unibas.ch/personen/profil/person/kleiber/) and [Achim Zeileis](http://eeecon.uibk.ac.at/~zeileis/ |
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This post examines the features of [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown) | |
using [knitr](http://yihui.name/knitr/) in Rstudio 0.96. | |
This combination of tools provides an exciting improvement in usability for | |
[reproducible analysis](http://stats.stackexchange.com/a/15006/183). | |
Specifically, this post | |
(1) discusses getting started with R Markdown and `knitr` in Rstudio 0.96; | |
(2) provides a basic example of producing console output and plots using R Markdown; | |
(3) highlights several code chunk options such as caching and controlling how input and output is displayed; | |
(4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and | |
(5) discusses the implications of R Markdown. |
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<script type="text/javascript" | |
src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"> | |
</script> | |
<script type="text/javascript">MathJax.Hub.Config({tex2jax: {processEscapes: true, | |
processEnvironments: false, inlineMath: [ ['$','$'] ], | |
displayMath: [ ['$$','$$'] ] }, | |
asciimath2jax: {delimiters: [ ['$','$'] ] }, | |
"HTML-CSS": {minScaleAdjust: 125 } }); | |
</script> |
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<expt ability> | |
/preinstructions = (initial.instructions) | |
/blocks=[1=pm.simple; 2=pm.4choice; 3=ac.test.type] | |
</expt> | |
<data> | |
/columns=[date, time, build, subject, trialcode, blockcode, blocknum, trialnum, latency, response, pretrialpause, | |
posttrialpause, trialtimeout, blocktimeout, correct, stimulusitem, stimulusnumber, | |
display.height, display.width, | |
computer.cpuspeed, computer.os, |
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#http://jeromyanglim.blogspot.com.au/2012/05/how-to-plot-three-categorical-variables.html | |
library(ggplot2) | |
# Create some data | |
set.seed(4444) | |
Data <- expand.grid(group=c("Apples", "Bananas", "Carrots", "Durians", "Eggplants"), | |
year=c("2000", "2001", "2002"), | |
quality=c("Grade A", "Grade B", "Grade C", "Grade D", "Grade E")) | |
Group.Weight <- data.frame( | |
group=c("Apples", "Bananas", "Carrots", "Durians", "Eggplants"), |