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#roger peng's listlabeling challenge from | |
#http://simplystatistics.tumblr.com/post/11988685443/computing-on-the-language | |
#create three example variables for a list | |
x <- 1 | |
y <- 2 | |
z <- "hello" | |
#create the function | |
makeList <- function(...) { |
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#page 118 of the NHIS document | |
#ftp://ftp.cdc.gov/pub/health_statistics/nchs/dataset_documentation/nhis/2010/srvydesc.pdf | |
#displays the R code to load the persons file into R as a survey object | |
#the code below creates a slightly different survey object, one that includes appropriately-imputed income. | |
#this R code: | |
# reads the year 2000 personsx file into R | |
# reads in all five imputed income files | |
# merges the 2000 personsx file with the five imputed income files |
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title = "Let it be" | |
wow = "words of wisdom" | |
Verse.1 = | |
c( "When I find myself in times of trouble" , | |
"Mother Mary comes to me" , | |
paste( "Speaking" , wow ) , | |
title ) | |
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library(XML) | |
url <- "http://www.paperbackswap.com/api/v1/index.php?RequestType=RecentlyPosted&Limit=100" | |
u <- xmlParse( url ) | |
v <- getNodeSet( u , "/Response/Books/Book/ISBN-10" ) | |
w <- sapply( v , xmlValue ) |
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#create the remove NA function | |
no.na <- | |
function( x , value = FALSE ){ | |
x[ is.na( x ) ] <- value | |
x | |
} |
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# install mapping packages | |
install.packages( c( 'sp' , 'rgdal' ) ) | |
# load necessary libraries | |
require(sp) | |
require(rgdal) | |
# create a temporary file and directory | |
tf <- tempfile() ; td <- tempdir() |
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# setwd( "C:/My Directory/wwow/" ) | |
path.to.7z <- normalizePath( "C:/Program Files (x86)/7-zip/7z.exe" ) | |
library(stringr) | |
library(downloader) | |
library(raster) | |
library(rasterVis) | |
source_url( |
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xl <- seq( 0 , 10000 , 100 ) | |
my_title <- 'if we randomly choose X people from some population and determine that none have a disease,\nwe can be 95% confident that the population prevalence rate is below Y% for this particular affliction.' | |
plot( xl , qbeta(1 - 0.05, 1 , xl ) , ylim=c(0,.01),axes=F,xlab="",ylab="",main="\nhow rare is a rare disease?\n\nsurvey research does a lousy job of estimating prevalence rates for unlikely events") | |
axis(2, at=seq(0,.01,.001), lab=paste0(seq(0,.01,.001)*100,"%"), las=TRUE) | |
axis(1, at=seq(0,10000,1000), lab=prettyNum(seq(0,10000,1000),big.mark=","), las=TRUE) | |
text( 3500 , 0.0075 , label = my_title , cex = 1.5, adj=c(0,0)) | |
z <- data.frame( x = 0:100000 , y = qbeta(1 - 0.05, 1 , 0:100000 ) ) |
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# # # # # # # # # # # # # # # # # | |
# # set the working directory # # | |
# # # # # # # # # # # # # # # # # | |
# setwd( "C:/My Directory/SWMAP/" ) | |
# # # # # # # # # # # # # # # # | |
# # example survey data set # # | |
# # # # # # # # # # # # # # # # |
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library(downloader) | |
# install.packages( c("MonetDB.R", "MonetDBLite" , "survey" , "SAScii" , "descr" , "downloader" , "digest" , "stringr" , "R.utils" , "RCurl" ) , repos=c("http://dev.monetdb.org/Assets/R/", "http://cran.rstudio.com/")) | |
library(SAScii) # load the SAScii package (imports ascii data with a SAS script) | |
library(RCurl) # load RCurl package (downloads https files) | |
library(stringr) # load stringr package (manipulates character strings easily) | |
library(downloader) # downloads and then runs the source() function on scripts from github | |
library(MonetDB.R) # load the MonetDB.R package (connects r to a monet database) |