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doInstall <- TRUE | |
toInstall <- c("ggplot2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
ANES <- read.csv("http://www.oberlin.edu/faculty/cdesante/assets/downloads/ANES.csv") | |
ANES <- ANES[ANES$year == 2008, -c(1, 11, 17)] # Limit to just 2008 respondents, | |
head(ANES) # remove some non-helpful variables | |
# Fit several models with the same DV: |
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doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
toInstall <- c("ReadImages", "reshape", "ggplot2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Image URL: | |
allImageURLs <- c("http://media.charlesleifer.com/blog/photos/thumbnails/akira_940x700.jpg", | |
"http://upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg/402px-Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg", | |
"http://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Official_portrait_of_Barack_Obama.jpg/441px-Official_portrait_of_Barack_Obama.jpg", | |
"http://cache.boston.com/universal/site_graphics/blogs/bigpicture/obama_11_05/obama22_16604051.jpg", |
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# Highlighting clusters, with chull() | |
doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
toInstall <- c("ggplot2", "RColorBrewer") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Generate some data | |
nn <- 500 | |
myData <- data.frame(X = rnorm(nn), |
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doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
toInstall <- c("ggplot2", "reshape2", "RColorBrewer") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Generate a random matrix | |
# This can be any type of numeric matrix, | |
# though we often see heatmaps of square correlation matrices. | |
nRow <- 9 | |
nCol <- 16 |
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doInstall <- TRUE | |
toInstall <- c("ggplot2", "poLCA", "reshape2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
ANES <- read.csv("http://www.oberlin.edu/faculty/cdesante/assets/downloads/ANES.csv") | |
ANES <- ANES[ANES$year == 2008, -c(1, 11, 17)] # Limit to just 2008 respondents, | |
head(ANES) # remove some non-helpful variables | |
# Adjust so that 1 is the minimum value for each variable: | |
ANES <- data.frame(apply(ANES, 2, function(cc){ cc - min(cc, na.rm = T) + 1 })) |
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SmoothCoefficientPlot <- function(models, modelnames = "", removeintercept = FALSE){ | |
# models must be a list() | |
Alphas <- seq(1, 99, 2) / 100 | |
Multiplier <- qnorm(1 - Alphas / 2) | |
zzTransparency <<- 1/(length(Multiplier)/4) | |
CoefficientTables <- lapply(models, function(x){summary(x)$coef}) | |
TableRows <- unlist(lapply(CoefficientTables, nrow)) |
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doInstall <- TRUE | |
toInstall <- c("alphahull") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Generate some sample data: | |
myData <- data.frame(x = rnorm(500), y = rnorm(500)) | |
# With a unit-circle hole in the center: | |
myData <- myData[sqrt(rowSums(myData^2)) > 1, ] | |
plot(myData) |
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doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
toInstall <- c("sna", "ggplot2", "Hmisc", "reshape2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Empty ggplot2 theme | |
new_theme_empty <- theme_bw() | |
new_theme_empty$line <- element_blank() | |
new_theme_empty$rect <- element_blank() | |
new_theme_empty$strip.text <- element_blank() |
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# Let's say you have an R object that you'd like to share with someone else | |
# but, for whatever reason, it is necessary to share it in text form. | |
# Generate a random data.frame | |
set.seed(1337) | |
NN <- 10 | |
theData <- data.frame(Alpha = rnorm(NN), | |
Beta = rnorm(NN)) | |
theData$Gamma <- theData$Alpha * 2 + theData$Beta / 2 + rnorm(NN) | |
print(theData) |
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doInstall <- TRUE | |
toInstall <- c("Hmisc", "ggplot2", "proxy", "grid") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Example usage | |
x <- c(4,6,4,5,6,7) | |
y <- 1:6 | |
plot(x, y, "o", pch=20) # bezier() generates smoothed curves from these points | |
points(bezier(x, y), type="l", col="red") |
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