similar to: What ECDF function?

Hello all! I am once again analyzing patient survival data with chronic liver disease. The severity of the liver disease is given by a number which is continuously variable. I have referred to this number as "meld"--model for end stage liver disease--which is the result of a mathematical calculation on underlying laboratory values. So, for example, I can generate a Kaplan-Meier plot

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, 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

I'm looking for a package that has a start-of-the-art method of imputation of missing values in a data frame with both continuous and factor columns. I've found transcan() in 'Hmisc', which appears to be possibly suited to my needs, but I haven't been able to figure out how to get a new data frame with the imputed values replaced (I don't have Herrell's book). Any

I have a data frame: > head(df) Time Temp Conc Repl Log10 1 0 -20 H 1 6.406547 2 2 -20 H 1 5.738683 3 7 -20 H 1 5.796394 4 14 -20 H 1 4.413691 5 0 4 H 1 6.406547 7 7 4 H 1 5.705433 > str(df) 'data.frame': 177 obs. of 5 variables: $ Time : Factor w/ 4 levels

Given a dataset x, the ecdf is ecdf(x). Then I can use ecdf(x)(y) to find the percentile of y. Given the ecdf is there a way to determine what is the value of y that is the boundary of let's say 95 percentile? In other words, is there a function I can call on the ecdf like: fomeFunc( ecdf( x ), 0.95 ) Which will return the highest value of y, for which ecdf( y ) < 0.95? The only solution

Hi, i want to plot empirical cumulative density functions for two variables in one plot. For better visualizing the differences in the two cumulative curves I'd like to log-scale the axis. So far I found 3 possible functions to plot ecdf: 1) ecdf() from the package 'stats'. I don't know how to successfully set the log.scales? Combining two plots is not a problem: plot(ecdf(x1))

Hi All, I have codes as follows to get the ecdf plots: > day.hos2<-c(6,4,6,6,4,6,5,4,7,5,6,6,8,6,17,9,8,4,6,3,5,8,7,12,5,10,6,4,6 ,13,7,6,6,25,4,9,96,6,6,6,6,9,4,5,5,4,10,5,7,6) > day.hos3<-c(5,6,7,6,4,5,6,6,6,6,19,7,5,9,8,8,7,5,6,20,40,5,8,7,7,5,6,13, 11,9,4,6,9,16,6,7,6) > f<-ecdf(day.hos2) > plot(f,col.p='red',col.h='red') >

Hi all, given this example #start a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) length(a) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) length(b) out<-ks.test(log10(a+1),log10(b+1)) # max distance D

Hello: [Kindly Cc when replying] The question in a nutshell is this: Is there a more robust alternative to Ecdf ()? The details: I've used Ecdf () _a lot_ over the past few years and I have learned to live with its warnings. But I am running short on time and patience now [*] Here is a reproducible example: > library (Hmisc) > x <- read.csv ( file =

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 all, I would like to calculate the complementary cumulative distribution function. As it is known, the ccdf is the 1-ecdf(X)==1-F(x). (From ?ecdf help is shown that ecdf returns a function which is the F(x) I would like to use that function inside my function and after call curve (which accepts function as input). My code looks like that onVector<-seq(1:100)

Hi. I have the following two ecdf plots in one graph: plot( ecdf(....), do.points=FALSE, verticals=TRUE, main=paste("Ecdf of distances ",DIM,sep=""), col="red" ); lines( ecdf(....), do.points=FALSE, verticals=TRUE ); How do I change the color of the resulting graph? Adding col="red" to either plot or lines results in an error

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

How does one ideally handle and display multidimenstional contingency tables in R v. 2.6.2? E.g.: > prob1<- data.frame(victim=c(rep('white',4),rep('black',4)), + perp=c(rep('white',2),rep('black',2),rep('white',2),rep('black',2)), + death=rep(c('yes','no'),4), count=c(19,132,11,52,0,9,6,97)) > prob1 victim perp

Hello, I'd like to plot an empirical cumulative distribution function, except instead of the fraction of values < x, I'd like the fraction of values > x. I think this can be done using the ecdf function in {Hmisc}. I installed the package and loaded it. However, when following the example given in the documentation, I get an error: x <- rnorm(100) ecdf(x,what='1-F')

I have a csv file that has approximately 50k rows. In the first value of each row, a file name is listed, and there are 162 different file names. At the end of each row, there is a number value. What I would like to be able to do is for the 162 different files (or we could call them categories), is compute the ecdf for the values within that category. Then plot the ecdf for each file on the

Hi to all, maybe the last question was not clear enough. I did not found any hints how to decide whether it should use lower.tail or not. As it is an extra R-feature ( written in http://finzi.psych.upenn.edu/R/Rhelp02a/archive/66250.html ) I do not find anything about it in any statistical books of me. Regards Carmen

Hi to all, I found in the R-help archive how to calculate the p-value for a gee result: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/74150.html but there are two questions (I am afraid they are basic questions ...) 1. why is the result multiplicated with 2 2. how could I decide between lower.tail =TRUE and FALSE: example:

Hi all R users I would like to know how acess the coordinates of the ECDF object. I look for the example, in this part: ###################### print(ls.Fn12 <- ls(env= environment(Fn12))) ###################### but I do not know to extract the Y coordinate and put it in other variable. My objective is to make a plot and identify the points with labels. ############# Example by