similar to: Computing a CDF or many quantiles

Dear list, I was attracted to a comment that the cdf.compare in S+ is not available in R. I wonder if anyone have more information on this. Thank you. Ilham

Dear all, I am calculating the bivariate skew normal cdf in "sn" package using "pmsn" function. Although it is quite convenient ( thanks to prof. Azzalini) but it seems to be slow. For example, it takes about 1 minute in calculation of 100k of such cdf values. I am thinking to write a c++ code for this although not very familiar with it. Any other idea?    Thanks in advance,

Dear all, How can I use the histogram density estimate (hist) to find the value of the cdf at a certain point? Thanks Maram [[alternative HTML version deleted]]

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

Dear R helpers I am trying to fit the Gumbel distribution to a data. I am using lmom package. I am getting problem in Cumulative Distribution Function of Gumbel distribution as I am getting it as a series of 0's and 1's thereby affecting the P P Plot. My R code is as follows. library(quantreg) library(RODBC) library(MASS) library(actuar) library(lmom) x <-

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, This is not an R question, but can anyone please point me to C/Fortran (C preferred) code which calculates the non-central t-density or the cdf? Many thanks and best wishes! GT

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Hello, In my simulations, I have to use the values of the cumulative distribution function of a multivariate normal with known mean vector and dispersion matrix. Please, can you tell me if there is a package in R to do that? Thank you very much for your greatly appreciate cooperation. Bernard Colin Colin Bernard Professeur titulaire Département de Mathématiques Faculté des Sciences Université

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

Hello all, I was wondering if there is an R function to do the following: [*] log(pnorm(x)-pnorm(y)), where x>y. I don't want all the area under the natural log of the normal pdf less than x, I only want the area between y and x. I am aware of the ability to specify log.p=TRUE, which gives me the log of the probability that X<=x. This does not help me, because the following code:

-- R Help List -- I am looking for a bivariate normal cdf routine in R. I have some fortran routines for this, which appear to be based on 15-point quadrature. Any guidance/suggestions on making these in loadable R-functions would be appreciated. Thanks, Dan =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= Daniel A. Powers, Ph.D. Department of Sociology University of Texas at Austin

Dear R-users, I have been using the code below in order to verify how the CDF of a skew-normal distribution was calculated: library(sn) s=seq(-30,30,by=0.1) a<-matrix(nrow=length(s),ncol=5) lambda=1 for(i in 1:length(s)){ a[i,1]=pnorm(s[i],mean=0,sd=1); a[i,2]=T.Owen(s[i],lambda); a[i,3]=a[i,5]-2*a[i,6]; a[i,4]=pnorm(s[i])-2*T.Owen(s[i],lambda);

Hello, I have to make use of the Cohen-Daubechies-Fauraue (CDF) 9/7 wavelet-transform, but have not found these biorthogonal wavlet in the released packages waveslim, wavethresh or wavelets. Is there any package doing this transform? Or can anybody send me the function doing this? I would be very grateful of that. Thanks Annika

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

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

Hi, I'm trying to find a way to take evaluate the Normal CDF over an interval and return the result on the log scale. This works, but I think it isn't numerically stable: log(pnorm(a, mean = x, sd = y) - pnorm(b, mean = x, sd = y)) Does anyone know of a single function that does the above? Or knows of a way to make it more stable? I'd really appreciate any suggestions!

Good day everyone, I want to assess the error when fitting a Gram-Charlier CDF to some data 'ws', that is, I want to calculate: Err = |ecdf(ws) - GCh_ser(ws)| The problem is, I cannot get the F(x) values from the ecdf. 'Summary(ecdf())' returns some of the x-axis values, but how do you get the F(x) values? Thank you for any help you can provide. Regards, Augusto

Hi, I would like to use the following codes to plot the CDF for pareto distribution. Before doing this, I have plot the emperical one. x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4477557,), col="red") Could anyone give me some advice whether the above codes are correct? Many thanks. -- View this message in context: