similar to: weighted cumulative distribution with ggplot2

hi all: ecdf() is the empirical cumulative distribution function, but I need the INVERSE cumulative distribution. how can I calculate it? thank you in advance /salva

Hi, I have two variables ranging both from 0 to 1 (n=500 each). Now I am interested in plotting them both in one plot (using ggplot2). So far I used ecdf() (from an example I found with google) to get values for the cumulatice distribution function which gives a relative curve. I also want to do the same plot but using absolute cumulative values instead of relative. Can that be done with ecdf or

Hi, all ecdf function (Empirical Cumulative Distribution Function) in "stats" package counts from smaller values to larger values. However, I want to draw it by counting from larger value to smaller values and I couldn't find options for this purpose. How can I draw ecdf or ecdf like graph by counting from larger values to smaller values. Thank you in advance. Hyunchul Kim

Hi R users, I am a new user, still learning basics of R. Is there anyway to extract y (or x) value for a known x (or y) value from ecdf (empirical cumulative distribution function) curve? Thanks in advance. Mano. [[alternative HTML version deleted]]

Dear list, I would like to plot the empirical cumulative distribution of the time needed by a treatment to attain a certain goal. A number of experiments is run with a strict time limit. In some experiments the goal is attained before the time limit, in other experiments time expires before the goal is attained. The situation is very similar to survivial analysis with censored data. I tryed

I have been using the ECDF function in the Hmisc package to produce cumulative distribution function plots. The problem is that for small datasets the steps "look bad" (not my characterization but from the client). Is there a way to get the same information but smoothed? I have tried the densityplot (lattice), which gives a smoothed line, but this does not give the cumulative density.

hi y'all, I am wondering if there is any special command, function, package, etc to help me doing a cumulative distribution function, with y-scale - probability scale. I tried the help in R and i got the following answers: cumsum(base) Cumulative Sums, Products, and Extremes ecdf(stepfun) Empirical Cumulative Distribution Function cpgram(ts) Plot

Dear R Users, Does R have an "inverse empirical cumulative distribution" function, something one can use to invert ecdf ? Thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. In the event you

Hello there, I am using R to plot some cumulative histogram for my data. Please help in this case. Thank you Lisa Wang Princess Margaret Hospital Toronto phone 416 946 4501 ext.4883

Hi, Here are three plots: library(ggplot2) data(diamonds) randind <- sample(nrow(diamonds),1000,replace=FALSE) dsmall <- diamonds[randind,] qplot(carat, data=dsmall, geom="histogram",binwidth=1) qplot(carat, data=dsmall, geom="histogram",binwidth=.1) qplot(carat, data=dsmall, geom="histogram",binwidth=.01) What are ways to put these three plots on a single

Hi All, Can you please help me, why this code in not generating line chart? library(ggplot2) par(mfrow=c(1,3)) #qplot(TIME1, BASCHGA, data=Orange1, geom= c("point", "line"), colour= ACTTRT) unique(Orange1$REFID) -> refid for (i in refid) { Orange2 <- Orange1[i == Orange1$REFID, ] pdf('PGA.pdf') qplot(TIME1, BASCHGA, data=Orange2, geom= c("line"),

In the area plots below, I see 4 triangle ticks at both sides of the bar; I believe these are non-stacked values for p, but they are definitively confusing. In addition, I would like to get the order of the colors in the plot the same as in the legend, and not arranged alphabetically (the factor is ordered, don't touch my order). Hadley once mentioned an undocumented aestetics

Hi, ggplot/qplot is great - it has really helped me do some nice things. However, simple boxplot of different columns/variables is a bit tricky, because of (i think) qplot's generic Y conditional on X input form. Se below. # Some data: a <- rnorm(100) b <- rnorm(100,1,2) c <- rnorm(100,2,0.5) # normal boxplot of a,b,c boxplot(a,b,c) # Looks good library(ggplot2) # loads qqplot2 #

Hello all, I'm stuck with a strange issue with writing jpegs of plots to a folder in a loop. This works: for (step in 1:length(steps)) { jpeg(filename=paste("frame_",sprintf("%05d",step),".jpg",sep="")) plot(steps[[step]]) dev.off() } But if I use qplot to generate the plot (which is my aim): for (step in 1:length(steps)) {

Hi All, I have a scatter plot produced using ggplot2 and I want to add the regression line to this scatter plot. I suppose I can use geom_smooth() to do this, but for the sake of learning ( I am new both to R and ggplot2), I want to try and add it as a function (something that curve() does in the standard R plotting). I did some search and found that stat_function() can be used for this. But

Hello, this following code give a nice png: /library(ggplot2) i <- 1 png(file=paste('test ',i,'.png',sep='')) qplot(carat, data=diamonds, fill=color,geom='histogram')+scale_y_continuous(i) dev.off() / I would like to get more files, but the following code doesn't make any file: /library(ggplot2) for (i in 1:2) { png(file=paste('test

Hi, I'm trying to create a stacked bar plot using ggplot2. Rather than plotting the count of each of the 13 "Bar" factors on the Y axis, I would like to represent the sum of the Values associated with each of the 13 "Bar" factors. Is there a way to do that? Given the following data, that would obviously mean that there would be some negative sums represented. Here's

Hi, in R there is the function "density" which computes kernel density estimates. Is there a "cumulative" version of it? Something like they have in Matlab: http://www.mathworks.nl/help/toolbox/stats/ksdensity.html I know there is ecdf, but I'm not sure it's based on kernel density smoothing. Thanks -- View this message in context:

HI am plotting different density plots in one graph each with a different color. And i want to add labels to plot mentioning which color belongs to which data series. p2 <- qplot(corArms, data = data1, geom = "density", adjust=0.4, main="Arms Correlation All") + layer(data=data2, geom="density", adjust=0.4, color=I(2)) + layer(data=data3,

Hi Folks, First, the important information. > sessionInfo() R version 2.12.1 (2010-12-16) Platform: i386-pc-mingw32/i386 (32-bit) Second, my problem. I have a series of data sets comprised in the following format. > totsoc Location Year Value 1 SOUTH 1998 29 2 SOUTH 1999 20 3 SOUTH 2000 32 4 SOUTH 2001 29 5 SOUTH 2002 25 6 SOUTH 2003 28 7