similar to: OT: code for non-central t-density/cdf

Looks like the files did not go through again. In any case, here is the kinv: please cut and paste and save to a file: -1.16801E-03 -2.24310E-03 -1.16864E-03 -2.24634E-03 -1.17143E-03 -2.25358E-03 -1.17589E-03 -2.26484E-03 -1.18271E-03 -2.27983E-03 -1.19124E-03 -2.29896E-03 -1.20164E-03 -2.32206E-03 -1.21442E-03 -2.34911E-03 -1.22939E-03 -2.38073E-03

Hi, I am wondering where the library file for R's nmath routines are? Doing a search on libR gave me the following: /usr/lib/libRKC16.so.1.2.0 /usr/lib/libRKC.so.1.2.0 /usr/lib/R/lib/libRlapack.so /usr/lib/R/lib/libR.so /usr/lib/libRKC.so.1 /usr/lib/libRKC16.so.1 None of these have the functions in nmath. Any help? Many thanks and best wishes! GT

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

Sorry, forgot to switch the header to the R group.... --- Globe Trotter <itsme_410 at yahoo.com> wrote: > Date: Thu, 2 Mar 2006 19:35:21 -0800 (PST) > From: Globe Trotter <itsme_410 at yahoo.com> > Subject: Re: [R] calling R's library using C > To: Dirk Eddelbuettel <edd at debian.org> > > Hi, Dirk: > > Thanks for all the help. I thought I would

R version: 0.62.1 (June 15, 1998) I just very naively attempted to grab the 'bicreg' package for Bayesian model selection from the StatLib library, and get it running under R. I've hit a brick wall very quickly, and as an R novice I'm not sure where to go next. Here's what happened: > bicreg(as.matrix(hiv[,c(-17,-18)]),as.matrix(hiv[,18])) Error: invalid formula >

Hi, I have a 324X15 matrix (No of years vs. heavy precipitation days) and I want to calculate the cdf at 5 different data points for each row. I tried by the following codes but it's not working. heavyprec <- read.csv (file="heavyprecdays_CSV.csv",header=TRUE,sep=",") a <- heavyprec pdf <- density (a, bw="SJ", kern= "gaussian") f <-

Hi, I am a new CentOS user (quite familiar with Fedora 1-23+) and I decided to try a new install of CentOS on a ASUS R503U. However, I can not get hibernate to work. I try: systemctl hibenaate and I get: Failed to execute operation: sleep verb not supported Btw, the problem does not go away with super-user. I was wondering how to get around this issue. I would like the abililty to hibernate

Hi For bureaucratic reasons beyond my control I need to rewrite an R function (for producing operating characteristic curves) as an Splus function ( version 6 , windows XP ). The R function makes extensive use of the fact that the student's t distribution function pt() has a non-centrality parameter built in ... sadly that parameter is not present in the Splus pt() function .

Hi, It is my understanding that the eigenvectors of a circulant matrix are given as follows: 1,omega,omega^2,....,omega^{p-1} where the matrix has dimension given by p x p and omega is one of p complex roots of unity. (See Bellman for an excellent discussion on this). The matrix created by the attached row and obtained using the following commands indicates no imaginary parts for the

Hi, I have read R's Writing Extensions manual and am still confused about how to use some of the routines there when I call from C. Specifically, I am writing a little test function which I will optimize using the nmmin function which underlies R's optim() with Nelder-Mead. I guess I wonder what library/header files I should be using. I was using R_ext/Applic.h and linking with libR but I

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

My machine has 8GB memory. I had quit all other programs that might take a lot of memory when I try the script (before I post the first message in this thread). The cdf file is of only 741 MB. It is strange to me to see the error. On Mon, Dec 28, 2009 at 2:38 AM, Wolfgang Huber <whuber at embl.de> wrote: > Dear Peng Yu > > how big is the RAM of your computer? You could try with

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))

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

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 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?

Greetings all, I'm trying to figure out how to calculate the inverse CDF (i.e. a quantile) for a non-central F distribution. I could put together a quick numerical solver routine using the CDF, but I wonder if there's a function that I've missed that would be more efficient? Thank-you, Andrew Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885

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: