similar to: time series problem: time points don't match

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

I'm trying to connect to vbox hypervisor on an Ubuntu 10.04 machine through libvirt java binding (libvirt-java-0.4.6) by simply invoking: Connect conn = new Connect("vbox:///session", false); but I got this exception: libvir: warning : Failed to find the interface: Is the daemon running ? libvir: Remote error : unable to connect to '/var/run/libvirt/libvirt-sock':

Dear All: In the attached file, I have 3 group patients, and there are 5 in each group (the groups are decided by the prefix of the idno). I want draw a repeat measurement comparison figure. My goal is to list 5 patients from same group on one horizontal line. But xyplot sounds pick them randomly (or I was confused?). Could you please help me modify the following code to accomplish this?

Dear list, I have a question concerning the above mentioned methods in the pls package with respect to the loadings matrix produced by the call. In some work I am doing I have found that the values produced are nearly of the same magnitude but of opposite sign. When I use the example data (sensory) I find this result reproduced. I am prepared to work this through but I have a feeling that

i am trying to make calls between two workstations using netmeeting and asterisk. i get the popup on both when i call the extensions 665 and 667 but when accept, i get this error *CLI> 0:18.190 H225 Caller:8112978 H225 Received connect PDU. 0:18.288 H245:810b388 H245 Read error: Bad file descriptor 0:18.318 H323 Cleaner H323

Dear R-users Please excuse me if this topic has been covered before, but I was unable to find anything relevant by searching I am currently doing a comparison of two biological variables that have a highly significant linear relationship. I know that the p-value of linear regression is not so interesting in itself, but this particular value does raise a question. How does R calculate

Hello, I am entirely new to this list, and not very experienced with R yet (but very excited about it!!). I am struggling with a dataset of x and y coordinate points I am plotting as a density map as follows: trial <- read.csv(file="F12.csv", sep=",", skip=32, head=TRUE) trial.sub <- subset(trial, Seconds>=30) trial.sub <- subset(trial.sub, Seconds<=1830) d