similar to: ggplot2: modifying line width and background fill color for stat_smooth()

With ggplot2, I can plot the glm stat_smooth for binomial data when the response is binary or a two-level factor as follows: data("Donner", package="vcdExtra") ggplot(Donner, aes(age, survived)) + geom_point(position = position_jitter(height = 0.02, width = 0)) + stat_smooth(method = "glm", family = binomial, formula = y ~ x, alpha = 0.2, size=2) But how can I

Hi, I am trying to learn to use ggplot2 for what I had hoped would be a fairly simple task. I have a relatively small data.frame (100 by 4). The first column contains symbols. The 2nd, 3rd and 4th columns represent percentage weightings for each symbol using 3 different methodologies. For example: sym <- make.unique(replicate(100, paste(sample(LETTERS, 3, replace = TRUE), collapse =

Dear all I would like to superpose some smoothing line through boxplot in ggplot > dput(ad) structure(list(konc.f = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,

Hi, # For publications, I am not allowed to repeat the axes. I have tried to remove the axes using: # yaxt="n", but it did not work. I have not understood how to do this in ggplot2. Can you help me? # I also do not want loads of space between the graphs (see below script with Dummy Data). # If I could make it look like the examples on the (nice) examples page: #

Hi all, I am using ggplot2 and continuing to find it very useful and pretty. However, I am trying to create some graphics for publication that would be included in an MS Word document (not my choice!) in Windows Vista. The problem is that I want to use stat_smooth() to add an fitted linear model line along with its 95% confidence band, but I cannot seem to get the confidence band in a format

Dear guRus, I am starting to work with the ggplot2 package and have two very dumb questions: 1) deterministic position_jitter - the jittering is stochastic; is there any way to get a deterministic jittering? For instance: example.data <- data.frame(group=c("foo","bar","foo","bar","foo","bar"),x=c(1,1,2,2,3,3),y=c(1,1,0,2,1,1))

I'm interested in creating a graphic -like- this: c <- ggplot(mtcars, aes(qsec, wt)) c + geom_point() + stat_smooth(fill="blue", colour="darkblue", size=2, alpha = 0.2) but I need to show 2 sets of bands (with different shading) using 5%, 25%, 75%, 95% limits that I specify and where the heavy blue line is the median. I don't understand how to do this with

Hello everyone, I was wondering if anyone was aware of a way in which I could use ggplot's stat_smooth() function for add an exponential moving average. I was thinking that I could maybe use something like: >myggplot + stat_smooth (method = 'HoltWinters( data , .9 , 0, 0)') but my efforts were futile. Perhaps there is a way to write my own custom method to throw into

Hi all, Does one of you know if there is any way to combine a "nls" method in the stat_smooth of ggplot? Regards -- ------------- Benoit Boulinguiez Ph.D student Ecole de Chimie de Rennes (ENSCR) Bureau 1.20 Equipe CIP UMR CNRS 6226 "Sciences Chimiques de Rennes" Avenue du G?n?ral Leclerc CS 50837 35708 Rennes CEDEX 7 Tel 33 (0)2 23 23 80 83 Fax 33 (0)2 23 23 81 20

Hello, I drew a simple area plot using ggplot2 using set <- read.table(file="http://www.jovian.nl/set.csv", head=1, sep=",") library(ggplot2) ggplot() + layer( data = set, mapping = aes(x = time, y = hours), geom = "area", stat="smooth", color="red" ) + layer( data = set, mapping = aes(x = time, y = hours), geom = "area",

I have a function: myplot <- function (X) { d <- plotCounts(dds2, gene=X, intgroup="condition", returnData=TRUE) png(paste("img/", X, ".png", sep="")) ggplot(d, aes(x=condition, y=count, color=condition)) + geom_point(position=position_jitter(w=0.1,h=0)) + scale_y_log10(breaks=c(25,100,400)) + ggtitle(X) +

> On Nov 2, 2017, at 9:27 AM, Ed Siefker <ebs15242 at gmail.com> wrote: > > I have a function: > > myplot <- function (X) { > d <- plotCounts(dds2, gene=X, intgroup="condition", returnData=TRUE) > png(paste("img/", X, ".png", sep="")) > ggplot(d, aes(x=condition, y=count, color=condition)) + >

I don't really understand. I mean, I understand the solution is print(ggplot(...)). But why is that required in a function and not at the console? Shouldn't I be able to rely on what I do at the console working in a script? Is this inconsistent behavior by design? On Thu, Nov 2, 2017 at 11:54 AM, David Winsemius <dwinsemius at comcast.net> wrote: > >> On Nov 2, 2017,

With this data x <- c(0,0,1,1,2,2) y <- c(5,6,4,3,2,6) lwr <- y-1 upr <- y+1 xlab <- c("Low","Low","Med","Med","High","High") mydata <- data.frame(x,xlab,y,lwr,upr) I would like to make a dot plot and use lwr and upr as error bars. Above 0=Low. I would like there to be some space between the 5 and the 6 corresponding

Hello R-users, I've been looking for a function performing one and two sample Hotelling test for testing equality of mean vectors. Has anyone implemented such a function in R? thanks a lot, Bill ============== Bill Donner Statistician

Hello Again... I?m making a faceted plot of a response on two categorical variables using ggplot2 and having troubles with the coloring. Here is a sample that produces the desired plot: compareCats <- function(data, res, fac1, fac2, colors) { require(ggplot2) p <- ggplot(data, aes(fac1, res)) + facet_grid(. ~ fac2) jit <- position_jitter(width = 0.1) p <- p +

L'entreprise Red Hat r?agit ? la crise... en supprimant une ?norme f?te d'entreprise. Au lieu de cela, ils ont d?cid? de donner l'argent ? l'?quivalent am?ricain des Restos du Coeur, soit quelque 800.000 repas: http://www.newsobserver.com/business/story/1314667.html J'ai toujours eu un faible pour Red Hat, mais l?, je les appr?cie carr?ment. Comme quoi l'esprit de

In the change log of ggplot2, version 0.7, I find this: "* scales: any point outside of limits is dropped (this was previously the behaviour for discrete scales, but not continuous scales)" and that makes sense for some applications. But what about if I want to summarize the data with a smooth, and (a) include the effect of all values, but (b) "zoom in" on the smooth by

Dear list members, I'm running some tests looking at differences between means for various levels of a factor, using Tukey's HSD method. I would like to plot the data as boxplots or dotplots, with horizontal significance lines indicating which groups are statistically significantly different, according to Tukey HSD. Here's a nice image showing an example of such a graphical

Two different ways: library(ggplot2) x=5 size=50 A=data.frame(X=sample(x, size, replace=T), Y=sample(x, size, replace=T),a=rep(1:2,each=25));A # Facetting qplot(X,Y,data=A) + geom_jitter(position=position_jitter(width=.03)) + facet_grid(.~a) # Or with vp p=qplot(X, Y, data=A) + geom_jitter(position=position_jitter(width=.03)) ggsave(p, file='main.png') p1=qplot(X, Y, data=A) +