Displaying 20 results from an estimated 10000 matches similar to: "R 2.2.2-1 RPM build problem and solution on RH AS 4 x86_64"
2006 Jul 04
1
problem getting R 2.3.1 svn r38481 to pass make check-all
Hi,
I noticed this problem on my home desktop running FC4 and again on my
laptop running FC5. Both have previously compiled and passed make
check-all on 2.3.1 svn revisions from 10 days ago or so. On both these
machines, make check-all is consistently failing (4 out of 4 attempts on
the FC 4 desktop and 3 out of 3 on the FC 5 laptop) in the
p-r-random-tests tests. This is with both default
2005 Aug 01
1
Follow-Up: R on FC4
Dear List,
A few weeks ago a discussion took place regarding Fedora Core 4 and
compiling R on that platform using the new version 4 of gcc and its
gfortran compiler.
gcc was recently updated to 4.0.1 on FC4 (4.0.1-5 in Red Hat Land) so I
thought I'd give compiling R a go on my laptop which needed updating
anyway. I've had trouble using the optimisation flags I used to use
under FC3 with
2005 Aug 14
1
make check-all fails (PR#8063)
Full_Name: Jed Kaplan
Version: 2.1.1 Patched
OS: Fedora Core 4
Submission from: (NULL) (66.31.221.212)
Installation through "make check" succeeds. "Make check-all" fails with the
following tail message:
"
make[3]: Entering directory `/mnt/linuxApp/usr/local/R/R-patched/tests'
running code in 'p-r-random-tests.R' ...make[3]: *** [p-r-random-tests.Rout]
Error 1
2012 Apr 22
1
Survreg
Hi all,
I am trying to run Weibull PH model in R.
Assume in the data set I have x1 a continuous variable and x2 a
categorical variable with two classes (0= sick and 1= healthy). I fit the
model in the following way.
Test=survreg(Surv(time,cens)~ x1+x2,dist="weibull")
My questions are
1. Is it Weibull PH model or Weibull AFT model?
Call:
survreg(formula = Surv(time, delta) ~ x1
2008 Oct 07
3
Fitting weibull, exponential and lognormal distributions to left-truncated data.
Dear All,
I have two questions regarding distribution fitting.
I have several datasets, all left-truncated at x=1, that I am attempting
to fit distributions to (lognormal, weibull and exponential). I had
been using fitdistr in the MASS package as follows:
fitdistr<-(x,"weibull")
However, this does not take into consideration the truncation at x=1. I
read another posting in this
2005 Aug 27
1
survival parametric question
Hi to all,
I am working on design package using survival function.
First using PSM and adopting a weibull specification for the baseline hazard , I have got the following results(since weibull has both PH and AFT propreties ,in addition I have used the PPHSm command):
Value Std. Error z p
(Intercept) 1.768 1.0007 1.77 7.73e-02
SIZE -0.707 0.0895 -7.90 2.80e-15
2002 Jan 17
1
weibull in R
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
2012 Feb 21
3
HELP ERROR Weibull values must be > 0
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
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2005 Nov 24
4
Survreg Weibull lambda and p
Hi All,
I have conducted the following survival analysis which appears to be OK
(thanks BRipley for solving my earlier problem).
> surv.mod1 <- survreg( Surv(timep1, relall6)~randgrpc, data=Dataset,
dist="weibull", scale = 1)
> summary(surv.mod1)
Call:
survreg(formula = Surv(timep1, relall6) ~ randgrpc, data = Dataset,
dist = "weibull", scale = 1)
2009 Mar 08
2
survreg help in R
Hey all,
I am trying to use the survreg function in R to estimate the mean and
standard deviation to come up with the MLE of alpha and lambda for the
weibull distribution. I am doing the following:
times<-c(10,13,18,19,23,30,36,38,54,56,59,75,93,97,104,107,107,107)
censor<-c(1,0,0,1,0,1,1,0,0,0,1,1,1,1,0,1,0,0)
survreg(Surv(times,censor),dist='weibull')
and I get the following
2011 Oct 28
1
weibull fitdistr problem: optimization failed
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
2012 Jan 26
1
3-parametric Weibull regression
Hello,
I'm quite new to R and want to make a Weibull-regression with the survival package. I know how to build my "Surv"-object and how to make a standard-weibull regression with "survreg".
However, I want to fit a translated or 3-parametric weibull dist to account for a failure-free time.
I think I would need a new object in survreg.distributions, but I don't know how
2010 Nov 15
1
interpretation of coefficients in survreg AND obtaining the hazard function
1. The weibull is the only distribution that can be written in both a
proportional hazazrds for and an accelerated failure time form. Survreg
uses the latter.
In an ACF model, we model the time to failure. Positive coefficients
are good (longer time to death).
In a PH model, we model the death rate. Positive coefficients are
bad (higher death rate).
You are not the first to be confused
2001 Aug 28
2
Estimating Weibull Distribution Parameters - very basic question
Hello,
is there a quick way of estimating Weibull parameters for some data points
that are assumed to be Weibull-distributed?
I guess I'm just too lazy to set up a Maximum-Likelihood estimation...
...but maybe there is a simpler way?
Thanks for any hint (and yes, I've read help(Weibull) ;)
Kaspar Pflugshaupt
--
Kaspar Pflugshaupt
Geobotanical Institute
ETH Zurich, Switzerland
2005 Nov 22
3
Weibull and survival
Hi
I have been asked to provide Weibull parameters from a paper using
Kaplan Meir survival analysis.
This is something I am not familiar with.
The survival analysis in R works nicely and is the same as commercial
software (only the graphs are superior in R).
The Weibull does not and produces an error (see below).
Any ideas why this error should occur?
My approach may be spurious.
2005 Jun 09
2
Weibull survival modeling with covariate
I was wondering if someone familiar
with survival analysis can help me with
the following.
I would like to fit a Weibull curve,
that may be dependent on a covariate,
my dataframe "labdata" that has the
fields "cov", "time", and "censor". Do
I do the following?
wieb<-survreg(Surv(labdata$time,
labadata$censor)~labdata$cov,
2009 Dec 06
2
MLE in R
Hi, dear R users
I am a newbie in R and I need to use the method of meximum likelihood to fit a Weibull distribution to my survival data. I use "optim" as follows:
optim(c(1.14,0.25),weibull.like,mydata=mydata,method="L-BFGS-B",hessian = TRUE)
My question is: how do I setup the constraints that the two parametrs of Weibull to be pisotive?
Many thanks! Any comments are
2012 Mar 05
1
Fitting & evaluating mixture of two Weibull distributions
Hello,
I would like to fit a mixture of two Weibull distributions to my data, estimate the model parameters, and compare the fit of the model to that of a single Weibull distribution.
I have used the mix() function in the 'mixdist' package to fit the mixed distribution, and have got the parameter estimates, however, I have not been able to get the log-likelihood for the fit of this model
2010 Jan 28
4
Problems with fitdistr
Hi,
I want to estimate parameters of weibull distribution. For this, I am using
fitdistr() function in MASS package.But when I give fitdistr(c,"weibull") I
get a Error as follows:-
Error in optim(x = c(4L, 41L, 20L, 6L, 12L, 6L, 7L, 13L, 2L, 8L, 22L,
:
non-finite value supplied by optim
Any help or suggestions are most welcomed
--
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2009 Apr 30
1
finite mixture model (2-component Weibull): plotting Weibull components?
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