similar to: mirror question

Hi, I would like to simulate data with a binary outcome and a set of predictors that are correlated. I want to be able to fix the number of event (Y=1) vs. non-event (Y=0). Thus, I fix this and then simulate the predictors. I have 2 questions: 1. When the predictors are continuous, I can use mvrnorm(). However, if I have continuous, ordinal and binary predictors, I'm not sure how to simulate

NOTE: posted this to gluster-devel when I meant to post it to gluster-users 01 | 02 mirrored --| 03 | 04 mirrored --| distributed 05 | 06 mirrored --| 1) Would this command work for that? glusterfs-volgen --name repstore1 --raid 1 clustr-01:/mnt/data01 clustr-02:/mnt/data01 --raid 1 clustr-03:/mnt/data01 clustr-04:/mnt/data01 --raid 1 clustr-05:/mnt/data01 clustr-06:/mnt/data01 So the

Hello, I have installed GlusterFS one month ago, and replication have many issues : First of all, our infrastructure, 2 storage array of 8Tb in replication mode... We have our backups file on this arrays, so 6Tb of datas. I want replicate datas on the second storrage array, so, i use this command : # gluster volume rebalance REP_SVG migrate-data start And gluster start to replicate, in 2 weeks

That took a while! I have the following stats: 4085169 files in both bricks3162940 files only have a single hard link. All of the files exist on both servers. bmidata2 (below) WAS running when bmidata1 died. gluster volume heal clifford statistics heal-countGathering count of entries to be healed on volume clifford has been successful Brick bmidata1:/data/glusterfs/clifford/brick/brickNumber of

Hi, Using libvirt for KVM, experimenting with live migration with the VM on storage shared in a mirrored GlusterFS or an active-active DRBD setup where QEMU/KVM runs on the hosts on both sides of the mirror, the live migration works great. What concerns me is finding a way if possible to prevent a situation where a particular VM is running on both hosts at once. Is there any way within libvirt in

I'm currently evaluating glusterfs to see if it will work for our needs. I've setup a little test environment with 3 fairly fast machines and 4 raid devices. When using gigabit ethernet between the 3 systems, I get about 14%-20% performance (vs using the filesystem locally) on large files and about .5%-17% performance on small files. I used bonnie++ for benchmarking. Since these numbers

I wonder if someone could explain the behavior of the anova() and lm() functions in the following situation: I have a standard 3x2 factorial design, factorA has 3 levels, factorB has 2 levels, they are fully crossed. I have a dependent variable DV. Of course I can do the following to get the usual anova table: > anova(lm(DV~factorA+factorB+factorA:factorB)) Analysis of Variance Table

Hi there, I've been using the SMATR package to do standardized major axis (SMA) regression on allometric data, and I've been able to to pairwise comparisons of slope & elevation between multiple study sites. Now I'm trying to do the same thing using major axis (MA) regression, but I'm getting errors (SMATR should be able to do MA as well as SMA regression for everything,

There are options that can help a little bit with the ls/find. Still, many devs will need to know your settings, so the volume's info is very important. Try the 'noatime,nodiratime' (if ZFS supports them). Also, as this is a new cluster you can try to setup XFS and verify if the issue is the same. RedHat provide an XFS options' calculator but it requires aby kind of subscription

Hello! I have a data frame A (below) with a grouping factor (group). I take my DV and create the new, lagged DV by applying the function lag.it (below). It works fine. A <- data.frame(year=rep(c(1980:1984),3), group= factor(sort(rep(1:3,5))), DV=c(rnorm(15))) lag.it <- function(x) { DV <- ts(x$DV, start = x$year[1]) idx <- seq(length = length(DV)) DVs <- cbind(DV, lag(DV,

I have 14,734 GFIDS that are different. All the different ones are only on the brick that was live during the outage and concurrent file copy- in. The brick that was down at that time has no GFIDs that are not also on the up brick. As the bricks are 10TB, the find is going to be a long running process. I'm running several finds at once with gnu parallel but it will still take some time.

Dear guRus, I am trying to replace "~" by "$\sim$" for TeX. However, I can't get the backslash to work. I would like to turn "DV~IV" into "DV$\sim$IV". sub("~","$\sim$","DV~IV") => "DV$sim$IV" sub("~","$\\sim$","DV~IV") => "DV$sim$IV"

Hi, I have simple installation, using mostly defaults, of two mirrored servers. One brick, one volume. GlusterFS version is 3.12.1 (server and client). All hosts involved are Debian 9.1. On another host I have mounted two different directories from the cluster using /etc/fstab: gfs1,gfs2:/vol1/sites-available/ws0 /etc/nginx/sites-available glusterfs defaults,_netdev 0 0 and

Hello! I have 2 variables - predictor "pred" and response variable "DV": pred<-c(439635.053, 222925.718, 668434.755, 194242.330, 5786.321, 115537.344, 100835.368, 7133.206, 159058.286, 4079991.629, 3380078.060, 2661279.136, 2698324.478, 1245213.965, 1901815.503, 1517019.451, 1396857.736, 1034030.988, 432249.574, 342329.325, 1831335.792, 2209578.859, 1641709.754,

We are about to abandon GlusterFS as a solution for our object storage needs. I'm hoping to get some feedback to tell me whether we have missed something and are making the wrong decision. We're already a year into this project after evaluating a number of solutions. I'd like not to abandon GlusterFS if we just misunderstand how it works. Our use case is fairly straight forward.

Hi, I''m new to puppet so apologises if this is obvious and only proves that I haven''t read the manual from cover to cover (oops, did I really to admit that! ;-) In the DebianRecipies example it uses the variable to determine the relative path to some template files. The variable has been set up at the node level however, there''s the possibility that it hasn''t

Hi all, I summarized actions on http://wiki.centos.org/SpecialInterestGroup/Virtualization/Status tagged with 06/05 The meeting LOG is below Regards Lars lars_kurth How do you want to run this? We have a set of lose ends: the roadmap via http://lists.centos.org/pipermail/centos-virt/2014-April/003763.html <http://lists.centos.org/pipermail/centos-virt/2014-April/003763.html> kbsingh

# I've tried to make this easy to paste into R, though it's probably so simple you won't need to. # I have some data (there are many more variables, but this is a reasonable approximation of it) # here's a fabricated data frame that is similar in form to mine: my.df <- data.frame(replicate(10, round(rnorm(100, mean=3.5, sd=1)))) var.list <- c("dv1",

Hi, this email is sent to flac-dev AT xiph DOT org, copied to matroska-devel AT lists DOT matroska DOT org, and David Bryant, the author of Wavpack4. We are about to implement the DV ( Digital Video ) video compression standard into matroska, to be able to offer an intelligent alternative to AVI for DV handling in editor tools. DV is using a high quality, high bitrate lossy video compression

This is a simple problem that has stumped me: I'm trying to loop through a few dozen variable names in graphs. I've tried various approaches like this: attach(mydata) ivs <- c("oneiv", "anotheriv", "yetanotheriv") dvs <- c("onedv", "anotherdv", "yetanotherdv") for (iv in ivs) { for (dv in dvs) { graphname <- paste(iv,