search for: 9.66

I am running samba-3.0.10 on a Solaris 8 box. The server is running as a DOMAIN_MEMBER in an Active Directory Domain. It has 8G of memory and 2 cpus. The smbd processes are started from inetd.conf. Lately, the server's load has been staying very high, from 10 - 14 and the smbd processes fluctuate between 1200 and 1600. This causes performance to suffer and clients start to complain that

Hi everyone, So I am trying to see which ecological parameter of different parks in nyc influence the most the diversity of the medium-sized mammals in those parks. I have a bunch of different parameters for each park I'm done studying and the presence (1) and absence (0) of each mammal. I wanted to do a principal component analysis of those data to know which ones of those parameters are the

Hi all. I have defined a plot thus: par(mar=c(5,5,4,5),las=1, xpd=NA) plot(Day, Ym1Imp, ylim=c(0,100), type="b", bty="l", main="Ym1 Expression", cex=1.3, xaxt="n", yaxt="n") #plot implant data axis(side=1, at=c(0,1,3,5,7,10,14,21), labels=c(0,1,3,5,7,10,14,21)) # label x axis mtext("Day", side =1, at=10, line=3, cex=1.2) # title x

Dear list, I'm currently trying to use the rms package to get predicted ordinal responses from a conditional ratio model. As you will see below, my model seems to fit well to the data, however, I'm having trouble getting predicted mean (or fitted) ordinal response values using the predict function. I have a feeling I'm missing something simple, however I haven't been able to

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

I am trying to do a MLE fit of the weibull to some data, which I attach. fitweibull<-function() { rt<-scan("r/rt/data2/triam1.dat") rt<-sort(rt) plot(rt,ppoints(rt)) a<-9 b<-.27 fn<-function(p) -sum( log(dweibull(rt,p[1],p[2])) ) cat("starting -log like=",fn(c(a,b)),"\n") out<-nlm(fn,p=c(a,b), hessian=TRUE)

I'm trying to write a function to find the means over factors of the responses in a mlm (something I would do easily in SAS with PROC SUMMARY). The not-working stub of a function to do what I want is below, and my problem is that I don't know how to call aggregate (or some other function) in the context of terms in a linear model extracted from a lm/mlm object. means.mlm <-

hi, so after upgrade to the current cvs all of our problem disappear:-) but we don't have time to test the ssl part... although after I compile and install the new dovecot I stop it I do a -------------------- find /home/*/Maildir -name '.imap*' -exec rm {} \; find /home/*/Maildir -name 'dovecot-uidlist' -exec rm {} \; find /home/*/Maildir -name 'msgid.cache' -exec rm

Dear R users, I try to write an rcode for a paranetric weibull model with unobserved heterogeneity. The data I have are giuven below. ( The data comes from Keiding and Klein artricle published in the Statistics in Medicine 1996) . While the simple weibull model runs perfectly ( I get -2*loglikelihood 1093,905), the weibull frailty model does not run well. The code I write is :

I am tying myself in knots over subscripts when applied to lists I have a list along the lines of: lis<-list(c("a","b","next","want1","c"),c("d", "next", "want2", "a")) >From which I want to extract the values following "next" in each member of the list, i.e. something along the lines of

Hi, LLVM 2.1-pre1 test results: Linux (SUSE) on x86 (P4) Release mode, but with assertions enabled LLVM srcdir == objdir # of expected passes 2250 # of expected failures 5 I ran the llvm-test suite on my desktop while I was also working on that PC, so don't put too much trust in the timing info. Especially during the "spiff" test the machine was swapping

Dear R Helpers, A few weeks ago I asked for some help on how to accomplish modifications to data in a set of data frames. As part of that request I mentioned that I realized that one way to accomplish my goal was to put the data frames together in a list but that I was looking for a way to do it with data frames and a loop because I "believe the better thing is to work df by df for my

The following updates are released with the CentOS-5.10 Release Announcement. You can see the individual announcements by viewing the CentOS-CR-Announce Mailing List here: http://lists.centos.org/pipermail/centos-cr-announce/2013-October/thread.html If you want the updates as fast as possible during CentOS point releases, please consider enabling the CentOS Continuous Release Repository:

Hey, i want to define 3 ideal breaks (bin) for each variable one of those variables is attached in the previous email, i don't want to consider quartile method because quartile is not working ideally for that data set because data distribution is non normal. so i want you to suggest another method so that i can define 3 breaks with the ideal interval for Recency, frequency and monetary to

Hi Your statement about attaching data is problematic. We cannot do much with it. Instead use output from dput(yourdata) to show us what exactly your data look like. We also do not know how do you want to split your data. It would be nice if you can show also what should be the bins with respective data. Unless you provide this information you probably would not get any sensible answer. Cheers

Hi You expect us to solve your problem but you ignore advice already recieved. Your data are unreadable, use dput(yourdata) instead. see ?dput > test<-read.table("clipboard", heade=T) Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 115 did not have 6 elements What is ?ideal interval? can you define it? Should it be such to provide eqal

Hello, I'm working on RFM analysis and i wanted to define my own breaks but my frequency distribution is not normally distributed so when I'm using quartile its not giving the optimal results. so I'm looking for a better approach where i can define breaks dynamically because after visualization i can do it easily but i want to apply this model so that it can automatically define the

LLVMers, The 2.1 pre-release (version 1) is available for testing: http://llvm.org/prereleases/2.1/version1/ I'm looking for members of the LLVM community to test the 2.1 release. There are 2 ways you can help: 1) Download llvm-2.1, llvm-test-2.1, and the appropriate llvm-gcc4.0 binary. Run "make check" and the full llvm-test suite (make TEST=nightly report). 2) Download