similar to: help with the coordinates of the ECDF object

Full_Name: Martin Frith Version: R-2.0.0 OS: linux-gnu Submission from: (NULL) (134.160.83.73) I have large vectors containing 100,000 to 20,000,000 numbers. However, they only contain a few hundred *distinct* numbers (e.g. positive integers < 200). When I do ecdf(v), it either runs out of memory, or it succeeds, but when I plot the ecdf with postscript, the output is unnecessarily bloated

Hi! I've noticed the ecdf() R code (R ver. 2.5.0) contains two call to sort: --- [R-code] --- ecdf <- function(x) x <- sort(x) n <- length(x) if (n < 1) stop("'x' must have 1 or more non-missing values") vals <- sort(unique(x)) rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n, method

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

Hello, if I plot a horizontal line, e.g., plot(c(1,2),c(1,1),xlim=c(0,3),lwd=2,type="l") or plot(c(1,2),c(1,1),xlim=c(0,3),lwd=4,type="l") then the left end (1st example) or both ends (2nd example) of the lines are not rectangular but slanted on the graphical display (screen). That behavour first occurred when I was trying to plot a stepfun, e.g., y <-

Dear R users, I am trying to minimize the distance between my data points and theoretical gamma distribution over shape and scale parameters. the function "mde" from actuar package does it for empirical distribution function and theoretical gamma distribution. However, I would like to minimize the distance by using only the data between 0.1 and 0.9 quantiles. I cannot use ecdf in this

Hi, Newbie here. I read the R for Beginners but i still don't get this. I have the following data (this is just an example) in a CSV file: courseid numstudents 101 209 141 13 246 140 263 8 321 10 361 10 364 28 365 25 366 23 367

Hi, I am using ecdf-function and want to use the ecdf()-data-points for nls() as data-parameter. nls() expects 'list' or 'environment' as a data-type, knots(ecdf(mydata)) gives me 'numeric'. What should I do now? Thanks in advance - Jochen Here is the code: ################################################# # --- Fit --- # Gumbel-Dist-Function, cumulative,

Dear Group, I am using the ecdf function as follows: cawa.cdp <- ecdf(cawaocc$LEFF80) summary(cawa.cdp) Empirical CDF: 223 unique values with summary Min. 1st Qu. Median Mean 3rd Qu. Max. 0.07918 1.35700 1.68600 1.61000 1.91200 2.70000 I can see by the summary that the y-value for the 3rd quartile is 1.912. How can I obtain the x-value for a specified y-value (e.g., 0.8)?

Hi, I have a question for the group, perhaps someone can help me figure this out. I've already looked in the help files and they were no help to me. I have a vector of values and I am plotting an ecdf graph. 1. How can i draw a continuous line through the ecdf points? (lines and type for the plot with an ecdf object does not work) 2. Supposing I have this line drawn. I can add a

Dear R-devel, The following line crashes R > approx(1, 1, 0, method='const', rule=2, f=0, yleft=NULL, ties='ordered')$y Process R:2 exited abnormally with code 5 at Tue Jul 21 14:18:09 2009 > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 9.1 year

Dear useRs, I have this dataset (D) with three columns. > dput(D) structure(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 2.990484802, 3.005018792, 3.019552781, 3.03408677, 3.048620759, 3.063154749, 3.077688738, 3.092222727, 3.106756717, 3.121290706, 3.135824695, 3.150358684, 3.164892674, 3.179426663, 3.193960652, 3.208494642, 3.223028631, 3.23756262,

Dear all, I have run into a problem when running some code implemented in the Bioconductor panp-package (applied to my own expression data), whereby gene expression values of known true negative probesets (x) are interpolated onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after updating

Thank you very much peter. It worked out nicely. I have additional question. How can I get Y-axis on log-scale? Thank you very much in Advance, Eliza UoS PP ________________________________ From: PIKAL Petr <petr.pikal at precheza.cz> Sent: 23 November 2017 16:22:39 To: Eliza Botto; r-help at r-project.org Subject: RE: adding percentage secondary y-axis Hi It is usually not

Dear UseRs, maybe is a silly question: how can I get Empirical CDF values from an object created with ecdf()?? Using print I obtain: Empirical CDF Call: ecdf(t) x[1:57] = 4.1, 4.4, 4.5, ..., 491.3, 671.27 Thanks in advance. Regards, Vito Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific

How do I plot using multiple(2) y-axes? I have two series that use the same x-data, but have very different scales. Appreciate any feedback, Per Bak

#See David Williams' book "Weighing the odds", p286 y <- c(1.21, 0.51, 0.14, 1.62, -0.8, 0.72, -1.71, 0.84, 0.02, -0.12) ybar <- mean(y) ylength <- length(y) ybarv <- rep(ybar, ylength) x <- 1:ylength plot(x,y,asp=1,xlab="position",ylab="ybar",type="n",ylim=c(-1,1)) segments(x[1], ybar, x[ylength], ybar) segments(x,ybarv,x,y)

Dear R users, Quick question on the use of ecdf for producing a cumulative distribution function. After having produced a cumulative distribution using ecdf, I would like to extract the exact x-value for a given percentile. For example I can ascertain the 1st and 3rd quartile using the summary function: cawa.cdp <- ecdf(cawaocc$LEFF80) plot(cawa.cdp, ylab="Fn(x)")

hi all i have another probably simple question. I have three variables say x, y and z. x and y are quite large and z is relative small. how can one plot the three variables on the same graph with two separate axis? (one for x and y and the other for z) e.g. x<-c(101,110,150,167,120) y<-c(120,135,175,95,200) z<-c(0.001, 0.15, 0.6, 0.8, 1) regards Allan

I would like you consider that the function ecdf could be extended in the following way to handle weights when computing Empirical distribution Functions. There exist particular cases that supports this kind of extension, see for example: Rao, C. R., 1997. Statistic and True. Putting chance to work. World Scientific Publishing. Cox, D. R., 1969. Some Sampling Problems in Technology. New

Hi It is usually not recommended but if you insist maybe library(plotrix) ?twoord.plot twoord.plot(lx=D[,1],ly=D[,2], rx=D[,1], ry=D[,3]) or plot.yy(x=D[,1],yright=D[,3], yleft=D[,2]) which allows only one x axis (see below). Cheers Petr plot.yy <- function (x, yright, yleft, yleftlim = NULL, yrightlim = NULL, xlab = NULL, yylab = list(NA, NA), pch = c(1, 2), col = c(1,2), linky