similar to: Generating kml lines output

Hello, i have the following model, poi1<-glm(F~S+T+L+C,family=poisson,x=T) where F,S,T,L are metric and C is a factor variable with the levels "0", "1", "2", "3", "4", "5" and "6" if i do summary(poi1), i get the following Call: glm(formula = F ~ S + T + L + C, family = poisson, x = T) Deviance Residuals: Min

Dear R-users I analysed the same data set by two different ways; analysis of covariance by using lm and anova functions and multiple comparison by using simtest function in the multcomp library. The output from the analysis of covariance is; > y<-lm(D~Cond+Q1,data=x) > anova(y) Analysis of Variance Table Response: D Df Sum Sq Mean Sq F value Pr(>F) Cond 2

Hi, I have not yet found any solution to my troubles so I though maybe someone here could give me some help. We have a Linux server with a Scsi Raid 5 disk. We use it as Samba and Nfs server for Windows and Linux clients. It also exports through Samba a disk mounted through Nfs from another Linux server. Everything was working fine until we uppgraded the server to RedHat 7.2. Now, after e few

Looking for more ways to speed up R, I've found that large improvements are possible in the speed of "sum" and "prod" for long real vectors. Here is a little test with R version 2.11.1 on an Intel Linux system > a <- seq(0,1,length=1000) > system.time({for (i in 1:1000000) b <- sum(a)}) user system elapsed 4.800 0.010 4.817 > system.time({for (i

R 2.2.0 windows XP How can I perform a regression analyses using a vector of means, a variance-covariance matrix? I looked at the help screen for lm and did not see any option for using the afore mentioned structures as input to lm. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC, University of Maryland School of Medicine Claude D.

On 23.11.2012, at 15:12, john skaller <skaller at users.sourceforge.net> wrote: > > On 23/11/2012, at 5:46 PM, Sean Silva wrote: > >> Adding LLVMdev, since this is intimately related to the optimization passes. >> >>> I think this is roughly because some function level optimisations are >>> worse than O(N) in the number of instructions. >>