similar to: How to determine the quantile boundary from an ECDF?

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)")

> On Jun 15, 2017, at 12:37 PM, Andras Farkas via R-help <r-help at r-project.org> wrote: > > Dear All, > > we have: > > t<-seq(0,24,1) > a<-10*exp(-0.05*t) > b<-10*exp(-0.07*t) > c<-10*exp(-0.1*t) > d<-10*exp(-0.03*t) > z<-data.frame(a,b,c,d) > > res<-t(apply(z, 1, quantile, probs=c(0.3))) > > > > my

Dear All, we have: t<-seq(0,24,1) a<-10*exp(-0.05*t) b<-10*exp(-0.07*t) c<-10*exp(-0.1*t) d<-10*exp(-0.03*t) z<-data.frame(a,b,c,d) res<-t(apply(z, 1, quantile, probs=c(0.3))) my goal is to do a 'reverse" of the function here that produces "res" on a data frame, ie: to get the answer 0.3 back for the percentile location when I have

David, thanks for the response. In your response the quantile function (if I see correctly) runs on the columns versus I need to run it on the rows, which is an easy fix, but that is not exactly what I had in mind... essentially we can remove t() from my original code to make "res" look like this: res<-apply(z, 1, quantile, probs=c(0.3)) but after all maybe I did not explain

Dear List, I have some discrete data and want to calculate the percentiles and the percentile ranks for each of the unique scores. I can calculate the percentiles with quantile(). I know that "ecdf" can be used to calculate the empirical cumulative distribution. However, I don't know how to exact the cumulative probabilities for each unique element. The requirement is similar

It would depend on which one of the 9 quantile definitions you are using. The discontinuous ones aren't invertible, and the continuous ones won't be either, if there are ties in the data. This said, it should just be a matter of setting up the inverse of a piecewise linear function. To set ideas, try x <- rnorm(5) curve(quantile(x,p), xname="p") The breakpoints for the

Dear List: I am trying to find the area between two ECDFs. I am examining the gap in performance between two groups, males and females on a student achievement test in math, which is a continuous metric. I start by creating a subset of the dataframe male<-subset(datafile, female="Male") female<-subset(datafile, female="Female") I then plot the two CDFs via

I have a problem where I need to calculate the corresponding cohort percentile ranks for each of several variables. Essentially, what I need is a function that will calculate the distribution-free percentiles from each variable's data vector, returning a corresponding vector of percentiles: e.g.: percentile.my.data<-/function/(my.data) I tried to make ecdf() perform this task but

Dear all, I am familiar with obtaining the value corresponding to a chosen probability via the quantile function. Now I am facing the opposite problem I have a value an want to know it's corresponding percentile in the distribution. So is there a function for this as well? Thank you for your support in advance, Felix

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

Heeeelp Given this data x <- c(1,5,100,300,250,200,550,900,1000) > quantile(x) 0% 25% 50% 75% 100% 1 100 250 550 1000 When I run the quantile, I can only know the value of the nth percentile I want to know what's the percentile position of each items in the list Sample 1 = 100% on the list has 1 or more 5 = more than x% on the list has 5 or more 100 = more than x% on the

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, can anyone help me to figure out how to compute the percentile of an individual observation with respect to a reference distribution. What I mean is. Let's assume I have a vector consisting of 10 numbers {3,5,8,1,9,5,4,3,5.5,7} and I want figure out what percentile the number 4.9 corresponds to. I failed to find any reference to such a function, although I would assume this must

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