similar to: lmer() function

How can I abort running a script if I determine it's taking too long? Currently, I simply close the R window and re-open it. Thank you! -- View this message in context: http://www.nabble.com/Abort-run-tp23852410p23852410.html Sent from the R help mailing list archive at Nabble.com.

Dear all , I am trying to install a package by name 'netmodels' keep on getting the following error : > install.packages("netmodels") Warning in install.packages("netmodels") : argument 'lib' is missing: using '/usr/lib64/R/library' also installing the dependency ‘VGAM’ trying URL

Dear all R-users, I wanted to fit a Garch(1,1) model to a dataset by: >garch1 = garch(na.omit(dat)) But I got a warning message while executing, which is: >Warning message: >NaNs produced in: sqrt(pred$e) The garch parameters that I got are: > garch1 Call: garch(x = na.omit(dat)) Coefficient(s): a0 a1 b1 1.212e-04 1.001e+00 1.111e-14 Can any one

Dear all, Does the frailty.object$history[[1]]$theta returns the Variance of random effect? Why is the value different? Here is an example with kidney data: > library(survival) > data(kidney) > frailty.object<-coxph(Surv(time, status)~ age + sex + disease + frailty(id), kidney) > frailty.object Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id), data

Hi, sorry by this off. I'm still try to understand nested design. I have the follow example (fiction): I have 12 plots in 4 sizes in 3 replicates (4*3 = 12) In each plot I put 2 species (A and B) to reproduce. After a period I make samples in each board and count the number of individuals total (tot) and individuals A and B (nsp). Others individuals excepts A and B are in total of

I have a problem with running ubuntu inside xen (well, actually debian didn''t work either). Dom0: Linux libre 3.0.4-030004-generic #201108301138 SMP Tue Aug 30 11:42:30 UTC 2011 x86_64 x86_64 x86_64 GNU/Linux ########## cf-node0.cfg: # # Configuration file for the Xen instance cf-node0, created # by xen-tools 4.2.1 on Thu Sep 8 05:11:42 2011. # # # Kernel + memory size #

I have a function myFunction(beta,x) where beta is a vector of coefficients and x is a data frame (think of it as a matrix). I want to optimize the function myFunction() by ONLY changing beta, i.e. x stays constant, with 4 constraints. I have the following code (with a separate source file for the function): rm(list=ls()) source('mySourceFile')