similar to: Estimating Weibull Distribution Parameters - very basic question

Hello, I've fitted a parametric survival model by > survreg(Surv(Week, Cens) ~ C(Treatment, srmod.contr), > data = poll.surv.wo3) where srmod.contr is the following matrix of contrasts: prep auto poll self home [1,] 1 1 1.0000000 0.0 0 [2,] -1 0 0.0000000 0.0 0 [3,] 0 -1 0.0000000 0.0 0 [4,] 0 0 -0.3333333 1.0 0 [5,] 0 0

Hello all, to obtain a list of all objects in all search paths, I've found the following to work: > biglist <- sapply(1:length(search()), objects) This more obvious one, however, does not work: > biglist <- sapply(search(), objects) Error in pos.to.env(pos) : invalid argument Still, search() gives [1] ".GlobalEnv" "package:ctest" "Autoloads"

Currently (R-1.4.1 as well as R-devel, according to http://stat.ethz.ch/R-alpha/R-devel/library/base/html/par.html), the html version of help(par) shows [...] lab A numerical vector of the form c(x, y, len) which modifies the way that axes are annotated. The values of x and y give the (approximate) number of tickmarks on the x and y axes and len specifies the label size. The default

GUYS, I NEED HELP WITH ERROR: library(MASS) > dados<-read.table("mediaRGinverno.txt",header=FALSE) > vento50<-fitdistr(dados[[1]],densfun="weibull") Erro em fitdistr(dados[[1]], densfun = "weibull") : Weibull values must be > 0 WHY RETURN THIS ERROR? WHAT CAN I DO? BEST REGARDS [[alternative HTML version deleted]]

Hello, does anyone know of a quick way to create a data frame "like" another, but with more rows? What I'd like to do is this: if mydata is a data.frame like a b c 1 TRUE yes 2 FALSE no 3 TRUE yes I'd like to get mydata2 with the same column names and column types, but without the values and with more rows. All I could think of was to manually do

Hello, I'd like to propose an extension to the function summary.aov. In Splus (2000, I don't know about other versions), summary.aov allows a parameter ssType to be set to 1 or 3 (defaults to 1) to choose the type of Sums of Squares. I know I can get Type III SS in R with drop1(model), but including the functionality into summary.aov would, in my opinion, - yield a more usable table

Hello, first, I'd like to congratulate the core team to the new R version 1.1. I think it's a great update, with glimpses into an even greater future (tcltk!). While playing around with the new functions (on Win 95), I found the following: As the documentation states, when I generate a plot and save it with recordPlot, I can regenerate it by printing the variable: > plot(1:10) >

On Thu, Jun 22, 2000 at 05:01:32PM +0200, p.dalgaard@biostat.ku.dk wrote: > I think this is pretty certainly a bug, so I'm cc'ing this to r-bugs. > > -p > > Kaspar Pflugshaupt <pflugshaupt@geobot.umnw.ethz.ch> writes: > > As the documentation states, when I generate a plot and save it with > > recordPlot, I can regenerate it by printing the variable:

On Thu, Jun 22, 2000 at 05:01:32PM +0200, p.dalgaard@biostat.ku.dk wrote: > I think this is pretty certainly a bug, so I'm cc'ing this to r-bugs. > > -p > > Kaspar Pflugshaupt <pflugshaupt@geobot.umnw.ethz.ch> writes: > > As the documentation states, when I generate a plot and save it with > > recordPlot, I can regenerate it by printing the variable:

Hello, has anybody written a function to plot density ellipses (95%, 99% or anything) in a scatterplot? I found nothing in any package, nor in the list archives. There does seem to be a contributed package "ellipse" for S-Plus (on S-Archive), but it does a lot more than what I would need. Still, if anybody ported it to R, I'd be grateful for a link. I'm a bit afraid to try the

Hello, I'm using R 1.40 on MacOS X X.1.2 (installed via the fink package manager). To upgrade my installed packages, I tried to use update.packages() today. All went well for most packages, with the exception of KernSmooth and cluster. In both cases, libraries were not found although I think they are present. Here's what happened: ---------------------------------- >

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component Weibull mixture -- where the components have a large overlap, and I am trying to adapt the "mclust" package which concern to normal

I had run into problems when compiling some contributed packages to an installation of R 1.40 by fink on MacOS X. Namely, packages KernSmooth (2.22-7) and cluster (1.4-0) would not find required libraries, though those were present on the system. Jeff Whitaker, the maintainer of the R fink packages, kindly sent me this: > Kaspar: It's not looking in /sw/lib, where the libs are (the

I've figured out how to use optim (barely) to estimate 2 parameter = weibull distributions. I can't get over how easy this is. What I need to = do is use a weight in the observations..... For example,=20 the tree diameters and weights are are=20 4.70 , 100 6.00, 98 7.10, 75.0 8.10, 86.3 8.60, 80.456 8.90, 20.5 9.50, 16.6 11.40, 12.657 11.80, 12.47 14.50,

I'm trying to fit a Weibull distribution to some data via maximum likelihood estimation. I'm following the procedure described by Doug Bates in his "Using Open Source Software to Teach Mathematical Statistics" but I keep getting warnings about NaNs being converted to maximum positive value: > llfunc <- function (x) { -sum(dweibull(AM,shape=x[1],scale=x[2], log=TRUE))} >

Dear R users, This is a basic question. I want to fit a Weibull distribution. fitdistr(data, "weibull") works and it is a maximum likelihood fitting. Is it a good method ? Or is it better to write a function for the log-likelihood and the gradient and to use a numerical routine ? Fitdistr works for uncensored data, but what can I use for censored (and uncensored) data ? Thank you

Hello, I've a question concerning the behaviour of the "scale" function in the base package. I'm using R 1.1.1 on Windows 95. If I take a matrix with NA values, such as > tm <- matrix(c(2,1,0,1,0,NA,NA,NA,0), nrow=3) > tm [,1] [,2] [,3] [1,] 2 1 NA [2,] 1 0 NA [3,] 0 NA 0 and scale it, the columns containing NAs come out all NA: >

Hi, I want to pick 3 "integer" random numbers from 1 to 10. How to do this? Thanks, Yu-Ling Wu __________________________________________________ Do You Yahoo!? Get email at your own domain with Yahoo! Mail. http://personal.mail.yahoo.com/ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi all I try to make a weibull survival analysis on R. I know make this on GLIM, and now I try to make the GLIM exercice GLEX8 on R to learning and compare the test. The variables are: time censor group bodymass In GLIM I make: $calc %s=1 $ to fit weibull rather than exponential $input %pcl weibull $ $macro model group*bodymass $endmac$ $use weibull t w %s $ Then, GLIM estimate an alpha for the

I'm getting errors when running what seems to be a simple Weibull distribution function: This works: x <- c(23,19,37,38,40,36,172,48,113,90,54,104,90,54,157,51,77,78,144,34,29,45,16,15,37,218,170,44,121) rate <- c(.01,.02,.04,.05,.1,.2,.3,.4,.5,.8,.9) year <- c(100,50,25,20,10,5,3.3,2.5,2,1.2,1.1) library(MASS) x <- sort(x) tryCatch( f<-fitdistr(x, 'weibull'), error