search for: 21.13

Dear list, The below dataset and code creates a new dataset with the results from the function cor.test being performed on each individual ('Individual_ID') from my original dataset. How do I convert each variable from the cor.test results to a numeric data type, as it is passed into the new dataframe? For example, 'estimate', 'p.value', and 'conf.int' should be

Dear all, I would like to conduct a Pearson's correlation using cor.test separately for each individual in my data set. Each individual has nine observations of the measurement variable 'Delta13C'. I can figure our how to do it manually one 'Individual_ID' at a time, but I cannot figure out how to automate the process (a loop I am guessing). In addition, I would like to

Below I have written out some simplified data from my dataset. My goal is to interpolate Price based on timestamp. Therefore the closer a Price is in time to another price, the more like that price it will be. I want the interpolations for each St and not across St (St is a factor with levels A, B, and C). Unfortunately, I get error messages from code I wrote. In the end only IDs 10 and 14 will

In playing with dovecot director, a couple of things came up, one related to the other: 1) Is there an effective maximum of directors that shouldn't be exceeded? That is, even if technically possible, that I shouldn't go over? Since we're 100% NFS, we've scaled servers horizontally quite a bit. At this point, we've got servers operating as MTAs, servers doing IMAP/POP

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

I am running dovecot 2.1.7 on Debian Squeeze 64 bit, config information at the end of the email. I am working on a Kerberos/GSSAPI based setup that requires cross-realm authentication. I have regular GSSAPI working, I can log in using pam_krb5 with password based logins or with the GSSAPI support when using a kerberos ticket in the default realm. However when I attempt to authenticate using

Hello, we experience problems with dovecot configuration using the listescape plugin to allow dots in foldernames. In some mail clients, dot-containing folders won't show any subfolders. This seems to be related to the fact that the \HasNoChildren flag is set on such folders even if subfolders do exits. Here is an example from telnet session: * LIST (\HasNoChildren) "/"

Hello, Using the dataset below I produce a soil.texture plot (R code for this included at the end). One will notice I have plotted the points based on whether or not they are in a region called 'upstream' or 'downstream'. I'm curious if there is a way to somehow extract counts of the number of points (red points and blue points) falling within each classification (e.g. silty

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

On Mon, Dec 16, 2013 at 04:16:29PM -0800, Michael Dalton wrote: > Commit 2613af0ed18a ("virtio_net: migrate mergeable rx buffers to page frag > allocators") changed the mergeable receive buffer size from PAGE_SIZE to > MTU-size, introducing a single-stream regression for benchmarks with large > average packet size. There is no single optimal buffer size for all >

On Mon, Dec 16, 2013 at 04:16:29PM -0800, Michael Dalton wrote: > Commit 2613af0ed18a ("virtio_net: migrate mergeable rx buffers to page frag > allocators") changed the mergeable receive buffer size from PAGE_SIZE to > MTU-size, introducing a single-stream regression for benchmarks with large > average packet size. There is no single optimal buffer size for all >