wch

library(shiny)

# Example usage:
# lmGadget(mtcars, "wt", "mpg")
#
# Returns a list with two items:
#   $data: Data with excluded rows removed.
#   $model: lm (model) object.
lmGadget <- function(data, xvar, yvar) {
  library(miniUI)

tbates

The Difference Pool

1. Subjects: Population sample

• N must be over 500, preferably 2,000
• Ideally genetically informative

6. Recruitment

• Students
• Public advertisements

2. Content: There will be a set of basic features that will be tested at the outset

• Need to compromise on this. Perhaps 2-hours of testing in the first instance?

dmarcelinobr

# rm(list = ls())  # clear objects
# graphics.off()   # close graphics windows
 plot.new() # call new plot window 
x = seq(-5,5, length=250)
y = dnorm(x)
plot(x,y, las=1, ylab='dnorm', type='n', yaxs='i', ylim=c(0, 0.5))
x2 = seq(qnorm(0.95), 5, length=50)
y2 = dnorm(x2)
polygon(c(x2[1], x2, x2[length(x2)]),  c(0, y2, 0), border=NA, col='grey')
lines(x, y)

brandonb927

#!/bin/sh

###
# SOME COMMANDS WILL NOT WORK ON macOS (Sierra or newer)
# For Sierra or newer, see https://github.com/mathiasbynens/dotfiles/blob/master/.macos
###

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/5b3c8418ed42d93af2e647dc9d122f25cc034871/.osx

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.