similar to: How to make a smooth ( linear ) CDF plot? -- Thanks!

This question might seem silly, because I felt that it MUST be in the mailing list archives or help files somewhere, but I simply couldn't find it. I want to make some simple CDF (cumulative distribution function) plots to check whether distributions are Gaussian / normal. But in order to check how "normal" the distribution is, I really need the y-axis to be Gaussian as well

On my machine (Mac OS 10.5.6, R 2.8.1) the following plot is drawn such that a substantial portion of the descender of the title is covered by the plot: library(ggplot2) qplot(x=1:10,y=1:10,main='p q j g') -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University www.thatmike.com Looking to arrange a meeting? Do so at: http://www.timetomeet.info/with/mike/ ~

Hi, I would like to overlap the cdf curve for observed and generated data  Here is my code: plot(cdf,main ="CDF of the sum for winter season-Hume",cex.axis=1.2,xlab="Rainfall (mm)", xaxs="i",yaxs="i",col=c("black","red"), lty=c(1,1),ylab="Cumulative probability", xlim=c(0,800),lwd=1) lines(ecdf(datobs))

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Hi all, I have data from an experiment with 3 independent variables, 2 are within and 1 is between. In addition to the dependent variable, I have a covariate that is a single measure per subject. Below I provide an example generated data set and my approach to implementing the ANCOVA. However the output confuses me; why does the covariate only appear in the first strata? Presumably it should

Trying to install rsync on SCO Unixware 7.1.1 and 7.1.3 just running the configure file gives me the following error configure: Configuring rsync 2.6.9 configure: error: cannot run /usr/bin/posix/sh ./config.sub how do I resolve this? --------------------------------------------------------------------------- Homer Simpson: Oh, they have the Internet on computers now Joseph Heller: There is

Hi guRus, I'm looking for advice on a good way to approach analysis of some multi-level data I've obtained. I had humans classify words and measured response time. Words were 10 positive words ("happy", "joy", etc) and 10 negative words ("sad","grumpy", etc). Words were also presented in either white, red or green color. All variables were

Hi everybody, I tried to analyze a custom Affymetrix 3'-biased Array. So I wanted to make a cdf package. (My CDF file size is 1.12Go). I tried several methods but the same error occured Method 1 > #Set the working directory > setwd("D:/Analyse R/Cel files") > #library to create cdf env > library("makecdfenv") >#Create cdf environment >pkgpath

Hi all, I've noticed that many computational neuroscience research groups use MATLAB. While it's possible that MATLAB may have some features unavailable in R, I suspect that this may instead simply be a case of costly tradition, where researchers were taught MATLAB as students and pay for it as researchers because it's all they know. I'd like to attempt to break the cycle by

Full_Name: Michael Aaron Karsh Version: 2.8.0 OS: Windows XP Submission from: (NULL) (75.61.109.172) I tried using the lm function to regress the third column listed below on the second column listed below. It gave me an error message. My code is below. > HDISWLSdata=read.table("RHDISWLS.txt") > HDISWLSdata V1 V2 V3 1 DENMARK

Dear all, I have define a discrete distribution P(y_i=x_i)=p_i, which I want to plot a CDF plot. However, I can not find a function in R to draw it for me after searching R and R-archive. I only find the one for the sample CDF instead my theoretical one. I find stepfun can do it for me, however, I want to plot some different CDF with same support x in one plot. I can not manage how to do it with

Good Afternoon, I'm trying to create a cdf plot, with the following code. It works well, but I have little doubt, if you can help solve. When I create the plot, like the graph line would still not appear with point #cdf x<-table(Dataset$Apcode) View(s) hist(s) *plot(ecdf(x))* x<-1 37607 2 26625 3 5856 4 25992 5 30585 6 16064 7 9850 .. ... .. 186 52 -- View this message in

Hi all, I'm working with data to which I'm fitting three-parameter weibull distributions (shape, scale & shift). The data are of low sample sizes (between 10 and 80 observations), so I'm reluctant to check my fits using chi-square (also, I'd like to avoid bin choice issues). I'd use the Kolmogorov-Smirnov test, but of course this is invalid when the distribution

Given f, a pdf over a finite interval, is there any existing R function that can efficiently tabulate the cumulative distribution function for f, or produce all N+1 quantiles of the form i/N? "Efficiently" here means better than doing repeated integrations for each point.

Hello, I wanted to know if there is a simple way of getting the inverse cdf for a KDE estimate of a density (using the ks or KernSmooth packages) in R ? The method I'm using now is to perform a numerical integration of the pdf to get the cdf and then doing a search for the desired probablity value, which is highly inefficient and very slow. Thanks, -fj [[alternative HTML version deleted]]

Hi, I've estimated a simple kernel density of a univariate variable with density(), but after I would like to find out the CDF at specific values. How can I do it? thanks for your help, with it I am very close to finish my first little bit more serious work in R, Viktor

Referring to "Using R for Data Analysis and Graphics" by J H Maindonald, and available from the R site, I found the example on p.30 non-working: > stem(qqnorm(possum$hdlngth)) Error in stem(qqnorm(possum$hdlngth)) : 'x' must be numeric Since qqnorm(possum$hdlngth) plots, and > class(possum$hdlngth) [1] "numeric" , the problem must be here: >

Hi, I have a data set which is assumed to follow weibull distr'. How can I find of cdf for this data. For example, for normal data I used (package - lmomco) >cdfnor(15,parnor(lmom.ub(c(df$V1)))) Also, lmomco package does not have functions for finding cdf for some of the distributions like lognormal. Is there any other package, which can handle these distributions?

Hi all, Just a random shot in the dark. Does anyone have/know of a function for the CDF of a generalized error dist? -- Elliot Williams (ewilliams at ucsd.edu) Economics Department, UC San Diego -------------- next part -------------- An embedded message was scrubbed... From: Elliot Williams <ewilliams at ucsd.edu> Subject: [R] Generalized Error Distribution (Exponential Power) CDF?

> Almost any method of fitting a density estimate would work on > integrating (numerically) the result. it is a nice idea concerning the monotony property, which will be obtained automatically, but I am going to use results of approximation analytically > In particular, look at package polspline, where > p(old)logspline does the integration for you. thank you, I am going to