halpo

################################################################################
# Copyright 2011
# Andrew Redd
# 11/23/2011
#
# Description of File:
# Makefile for knitr compiling
# 
################################################################################
all:pdf  # default rule DO NOT EDIT

timelyportfolio

%% LyX 2.0.2 created this file.  For more info, see http://www.lyx.org/.
%% Do not edit unless you really know what you are doing.
\documentclass[english,nohyper,noae]{tufte-handout}
\usepackage{helvet}
\usepackage[T1]{fontenc}
\usepackage[latin9]{inputenc}
\usepackage{babel}
\usepackage[unicode=true,pdfusetitle,
 bookmarks=true,bookmarksnumbered=true,bookmarksopen=true,bookmarksopenlevel=1,
 breaklinks=true,pdfborder={0 0 0},backref=false,colorlinks=false]

jeromyanglim

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.

psychemedia

digraph G {

	subgraph cluster_1 {
		Rscript -> localDir;
		localDir -> Rscript;
		Rscript -> Sweave;
		Sweave -> TeX;
		TeX -> PDF [ label = "laTeX"]
		Rscript -> Rmarkdown;
		RCurl -> Rscript;

timelyportfolio

require(lattice)
require(latticeExtra)
require(directlabels)
require(reshape2)
require(quantmod)
require(PerformanceAnalytics)


data(managers)
managers[which(is.na(managers),arr.ind=TRUE)[,1],

bobthecat

library(twitteR)
library(ggplot2)
library(grid)

# download all that you can
pol <- userTimeline('BeijingAir', n=3200)
length(pol)
# 3200

myGrep <- function(x){

timelyportfolio

#look at steps in constructing a horizon plot version
#of http://www.mebanefaber.com/timing-model/
#do horizon of percent above or below 10 month / 200 day moving average

require(lattice)
require(latticeExtra)
require(quantmod)


#since we are focused on the horizon plot, let's just look at one stock

timelyportfolio

require(RColorBrewer)
require(quantmod)
require(PerformanceAnalytics)

data(managers)

#let's do managers from 2002 to 2004 to get positive and negative
x <- cumprod(1+managers["2002::2004"])[,1] - 1

#get some decent colors from RColorBrewer

timelyportfolio

require(fAssets)
require(latticeExtra)
require(quantmod)
require(PerformanceAnalytics)

#my.url will be the location of the zip file with the data
my.url="http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/48_Industry_Portfolios_daily.zip"
#this will be the temp file set up for the zip file
my.tempfile<-paste(tempdir(),"\\frenchindustry.zip",sep="")
#my.usefile is the name of the txt file with the data

cjbayesian

## Corey Chivers, 2012 ##
sim_bayes<-function(p=0.5,N=100,y_lim=20,a_a=2,a_b=10,b_a=8,b_b=3)
{
   ## Simulate outcomes in advance   
   outcomes<-sample(1:0,N,prob=c(p,1-p),replace=TRUE)
   success<-cumsum(outcomes)

   for(frame in 1:N)
   {
      png(paste("plots/",1000+frame,".png",sep=""))