Zecca Lehn ZeccaLehn

Calls a sound -- useful when waiting...

install.packages("beepr")
library(beepr)
beep(sound = 3, expr = NULL) #Fanfare!!

1: "ping"

Sets the working directory in R on a Linux system after and are replaced with actual folder names.

Alows for sharing code without each user having to change the HOME variable (e.g., "home/myMachine/Projects/First"

setwd(paste0(Sys.getenv("HOME"),"/<TopDir>/<Root>"))

For Windows, use proper slash direction and notation.

Shows function Internals

library(BayesianFirstAid)
debugonce(bayes.t.test) # turns off debugging for function after first run
bayes.t.test(co2)

Returns hidden and unhidden environments

Code I presented in Johns Hopkins Data Science Capstone:

Size of compressed file as percentage of the original file

                   Adaptive 
                   Huffman Lempel-Ziv
     LaTeX file     66%      44%
     Speech file     65%     64%
     Image file      94%     88%

http://www.data-compression.com/lossless.html

	# Loads current gist with function
	# https://gist.github.com/timelyportfolio/1405187
	# dev.off(); plot(1)

	library(devtools)
	source_gist("1405187")

	require(quantmod)
	require(PerformanceAnalytics)

	stringToChar<- function( example ){

	example <- as.character(example)

	letters <- strsplit(example,"")[[1]]

	for (i in letters[1:length(letters)] ) { print(i) }

	}

	# Quick GIST I wrote in the Data Science Capstone JHU forum (Dec 2014)

	# It appears if the one of us draws 5 random tweets or news excerpts as the grading criteria calls for,
	# the probability that none of the five match the top-word is 32.8%--assuming the
	# true accuracy of model is 20%.

	# Overall, if the top-word as criteria for success is used, where 4 reviewers using 5 random samples,
	# the probability that none of the 20 predictions match the top word is only 1.2%.

	# #Majority Vote Accuracy
	# For Johns Hopkins / Machine Learning in R

	# n <- 5 # Independent Classifiers
	# k <- 3 #
	#
	# accuracy <- 0.7
	#
	# majorityAccu(5, 3, .7) # 83.7% Accuracy
	# majorityAccu(101, 51, .7) #99.9% Accuracy

	#Search installed packages by first letter -- regardless of upper/lower case (by 's' here)
	grep("^[s]", attributes(installed.packages())$dimnames[[1]], value = TRUE, ignore.case = TRUE)