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...data = mel, statistic = mel.fun, R = 999, F.surv = mel.surv, G.surv = mel.cens, sim = "cond", cox = mel.cox, index = c(1, 8)) Bootstrap Statistics : original bias std. error t1* 0.09967665 0.03579701 0.04973614 I want to apply the Fast bootstrap method from Salibian-Barrera and Zamar (2003) and Salibian-Barrera, M., Van Aels, S. and Willems, G. (2007) to the previous example, i.e., to produce a confidence interval for the exponent of the coefficient of tumour thickness in the Melanoma dataset . Moreover, I want to compare the performance of the Fast bootstr...

...= mel, statistic = mel.fun, R = 999, F.surv = mel.surv, G.surv = mel.cens, sim = "cond", cox = mel.cox, index = c(1, 8)) Bootstrap Statistics : original bias std. error t1* 0.09967665 0.03579701 0.04973614 I want to apply the Fast bootstrap method from Salibian-Barrera and Zamar (2003) and Salibian-Barrera, M., Van Aels, S. and Willems, G. (2007) to the previous example, i.e., to produce a confidence interval for the exponent of the coefficient of tumour thickness in the Melanoma dataset . Moreover, I want to compare the performance of the Fast bootstr...

...= mel, statistic = mel.fun, R = 999, F.surv = mel.surv, G.surv = mel.cens, sim = "cond", cox = mel.cox, index = c(1, 8)) Bootstrap Statistics : original bias std. error t1* 0.09967665 0.03579701 0.04973614 I want to apply the Fast bootstrap method from Salibian-Barrera and Zamar (2003) and Salibian-Barrera, M., Van Aels, S. and Willems, G. (2007) to the previous example, i.e., to produce a confidence interval for the exponent of the coefficient of tumour thickness in the Melanoma dataset . Moreover, I want to compare the performance of the Fast bootstr...

...= mel, statistic = mel.fun, R = 999, F.surv = mel.surv, G.surv = mel.cens, sim = "cond", cox = mel.cox, index = c(1, 8)) Bootstrap Statistics : original bias std. error t1* 0.09967665 0.03579701 0.04973614 I want to apply the Fast bootstrap method from Salibian-Barrera and Zamar (2003) and Salibian-Barrera, M., Van Aels, S. and Willems, G. (2007) to the previous example, i.e., to produce a confidence interval for the exponent of the coefficient of tumour thickness in the Melanoma dataset . Moreover, I want to compare the performance of the Fast bootstr...

Hi there, I'm trying to install the package RcppArmadillo in my R 2.11.1 which I installed and regularly update via Ubuntu's repositories. When I try to install RcppArmadillo from CRAN I get: > install.packages('RcppArmadillo', lib='~/myRlibs') [...] g++ -shared -o RcppArmadillo.so RcppArmadillo.o fastLm.o -L/home/matias/myRlibs/Rcpp/lib -lRcpp

.... Incidentally our environment includes R 2.6.1, RHEL 5.1, Solaris 10, SGE (Sun Grid Engine) and OpenMPI 1.2.4 (SunHPC 7.1)). In researching previous work, the most promising approaches seem to be: A. Snow (with Rmpi or Rpvm) (as described in http://www.r-project.org/useR-2006/Slides/Harrington+Salibian-Barrera.pd f from the 2006 R User Conference) It is my understanding that this approach is viable, and works with OpenMPI 1.2.4. Is anyone using this method with good results? B. taskpR, RScaLAPACK, pMatrix I read a paper http://sdm.lbl.gov/sdmcenter/projects/SDM.center.parallel.r.2-pager.4.do c...

Sorry for re-posting, but the original one ended up inside a previous and unrelated thread. -- Matias ----- Hello, This simple SVD calculation (commands are copied immediately below) crashes on my Ubuntu machine (R 2.13.0). However it works fine on my Windows 7 machine, so I suspect there's a problem with (my?) Ubuntu and / or R. Can anybody else reproduce it (with Ubuntu 11.04)? Thanks

Dear All, When I run rlm to obtain robust standard errors, my output does not include p-values. Is there any reason p-values should not be used in this case? Is there an argument I could use in rlm so that the output does include p-values? Thanks in advance, Celso [[alternative HTML version deleted]]

Hello, This simple SVD calculation (commands are copied immediately below) crashes on my Ubuntu machine (R 2.13.0). However it worked fine with R.12 and Ubuntu 10.04, and it also works fine on my Windows 7 machine with R 2.13, so I suspect there's a problem with (my?) Ubuntu and / or R. I'm using the R distribution that is accessible with Ubuntu's repositories manager, I am not

Hello, I realize this is not a new problem, but I'm hoping somebody can point me in the right direction. The function silly() below calls gam() (from package gam) with different values of the span parameter for lo(), which is used inside the formula of gam. The values for span are stored in a vector that resides in the function silly(), and that lo(), for some reason, needs to see. A hack