Thomas Guenther dreammaster38

Marsaglia-polar.js

This script generates random numbers along a Normal or Log-normal distribution using the Marsaglia polar method.

There are four functions you can use:

normalRandom: Generate random numbers that follow a Normal distribution.
normalRandomInRange: Generate random numbers that follow a Normal distribution but are clipped to fit within a range
normalRandomScaled: Generate random numbers that follow a Normal distribution with a given mean and standard deviation
lnRandomScaled: Generate random numbers that follow a Log-normal distribution with a given geometric mean and geometric standard deviation

The introduction to Reactive Programming you've been missing

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

Install Vagrant

sudo su
apt-get update && apt-get install -y libvirt-dev ruby-all-dev apparmor-utils
curl -O -L https://dl.bintray.com/mitchellh/vagrant/vagrant_1.6.5_x86_64.deb
dpkg -i vagrant_1.6.5_x86_64.deb 
aa-complain /usr/lib/libvirt/virt-aa-helper # workaround
exit

	#List of most used R packages that we wish to install.
	libraries = c('cacheSweave', 'Deducer', 'devtools', 'doBy', 'foreign', 'gdata',
	'ggplot2', 'Hmisc', 'JGR', 'lubridate', 'maps', 'mapdata', 'mapproj',
	'maptools', 'proto', 'psych', 'R2wd', 'RCurl', 'reshape',
	'RODBC', 'roxygen2', 'seqinr', 'sm', 'sp', 'sqldf', 'survey',
	'WriteXLS', 'XML', 'xtable')

	#We will install packages from the main CRAN site
	repos = 'http://cran.r-project.org'
	#Site provides some prebuilt binaries for Windows

	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD

	shinyServer(function(input, output) {
	output$obs <- renderUI({
	sliderInput("obs", "Number of observations:",
	min = 10000, max = 90000,
	value = 50000, step = 10000)
	})
	output$distPlot <- renderPlot({
	if (!is.null(input$obs)) {
	dist <- NULL
	for (i in 1:input$obs) {

	license: mit
	height: 300
	scrolling: no
	border: no

	Copyright (C) 2016 Donnie Ray Jones

	Permission is hereby granted, free of charge, to any person obtaining a
	copy of this software and associated documentation files (the
	"Software"), to deal in the Software without restriction, including
	without limitation the rights to use, copy, modify, merge, publish,
	distribute, sublicense, and/or sell copies of the Software, and to
	permit persons to whom the Software is furnished to do so, subject to
	the following conditions:

	var mediaJSON = { "categories" : [ { "name" : "Movies",
	"videos" : [
	{ "description" : "Big Buck Bunny tells the story of a giant rabbit with a heart bigger than himself. When one sunny day three rodents rudely harass him, something snaps... and the rabbit ain't no bunny anymore! In the typical cartoon tradition he prepares the nasty rodents a comical revenge.\n\nLicensed under the Creative Commons Attribution license\nhttp://www.bigbuckbunny.org",
	"sources" : [ "http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/BigBuckBunny.mp4" ],
	"subtitle" : "By Blender Foundation",
	"thumb" : "images/BigBuckBunny.jpg",
	"title" : "Big Buck Bunny"
	},
	{ "description" : "The first Blender Open Movie from 2006",
	"sources" : [ "http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/ElephantsDream.mp4" ],