similar to: A Flash Mob for R Content on Stack Overflow: Tonite @ 7-9pm PST

R Folks - Last month, a group of R users gathered in San Jose and online with a goal: to populate a web-based resource -- Stack Overflow -- with some of the most often-asked and reluctantly-answered questions about R. I write to say thanks to those of you who participated, and encourage members of the R community to take a look at what's happened since, and possibly even contribute. A list

All Bay Area useR's, Quick reminder that our use R! Group 2009 kick off meeting is next Wednesday evening: http://www.meetup.com/R-Users/calendar/9573566/ at Predictive Analytics World. Panel Discussion - The R and Science of Predictive Analytics: Four Case Studies in R * Bo Cowgill, Google * Itamar Rosenn, Facebook * David Smith, Revolution Computing * Jim Porzak, The

Hi R folks, I'd like to announce several new R users groups here in SF, LA, NYC, and Ottawa - as well as their next scheduled event. The goal of these user groups, besides gently explaining 'drop=TRUE' to the uninitiated, is to exchange knowledge, promote best practices, and spur the adoption of R for innovative applications. If I've missed any groups here, please feel to add on

I will be creating the branch at 9PM PST. Please refrain from checking in any large changes until after the branch creation. I'm still seeing unexpected dejagnu failures for PPC and X86. Platform maintainers, please XFAIL these and file bugzilla bugs. Email me if you have concerns or questions. -Tanya

Dear sir,    How to do bilinear time series in R?Is there any functions or packages?  thank you! -----Sincerely yours Kuangnan Fang 方匡南 敬上 department of statistics ,Economics school,Xia men University. Fujian Province (361005) China Mobile Phone：15860721915 SKYPE: ruiqwy MSN Messenger: ruiqwy@hotmail.com QQ:39863401 --- 09年3月31日，周二, r-help-request@r-project.org

All, Tuesday week (July 15th) Mike Driscoll & I will be presenting "A Gentle Introduction to R and its Applications in Business Intelligence" at the SDForum Business Intelligence SIG in Palo Alto, California. One motivation is to judge interest in starting a Use R Group in the Bay Area. We will have an informal organizational meeting after the talk. We hope all local R

Hello again Max. A correction to my response from yesterday. Things were better than they seemed. I thought it over, checked Arellano's panel book and Driscoll and Kraay (Rev. Econ. Stud. 1998) and finally realized that vcovSCC does what you want: in fact, despite being born primarily for dealing with cross-sectional correlation, 'SCC' standard errors are robust to "both

All: Jan de Leeuw and I have taken the initiative to organize a R users group in Los Angeles with regular meetings. Our aim is to bring together practitioners (from industry and academia alike) in order to facilitate a free and open exchange of knowledge and experience in solving data analysis, statistical modeling, data mining, visualization, statistical computing etc. problems by using R.

G'day, Plot doesn't seem to work when I specify block as an error term, but does if I load block into the model as the first factor (see code below). Is there some way to make plot work with the fancier model specification? Also, if anyone knows how to get SEDs for this model I would really like to know. response<-c(rnorm(5,5,2),rnorm(5,12,2),rnorm(5,18,2),rnorm(5,12,2))

Hi all, Regular and avid readers of this column will know that Don Driscoll and I have recently posted two messages requesting assistance concerning an apparent failure of "se.contrast" to produce an se for a contrast. So far, an ominous silence rings in our ears, but read on Gentle Reader, and see if even the machinations of "debug" doesn't stimulate you to respond with a

Hello, With 7.1-RC2 : Dec 30 18:10:38 client1 kernel: FreeBSD 7.1-RC2 #0: Tue Dec 23 11:42:13 UTC 2008 Dec 30 18:10:38 client1 kernel: root@driscoll.cse.buffalo.edu:/usr/obj/usr/src/sys/GENERIC Dec 30 18:10:38 client1 kernel: Timecounter "i8254" frequency 1193182 Hz quality 0 Dec 30 18:10:38 client1 kernel: CPU: Intel(R) Core(TM)2 CPU 4300 @ 1.80GHz (1800.01-MHz K8-class CPU) Dec

Hello List, I''ve got Xen running on RHEL 4 using the mv /lib/tsl /lib/tsl.disabled short cut but its killing my performance, mouse hardly moves and takes an age for anything to render. There''s an rpm on the wiki to install a xenglibc for RHEL 3 and I''m just curious can I use this on RHEL 4? Failing that anyone have any advice on where to look for

The San Francisco Bay Area useR Group is very excited to host Hadley Wickham on Sep 17 for our Fall kickoff meeting. Details at http://www.meetup.com/R-Users/calendar/10446894/ This year we are moving our regular meeting monthly meeting to the 2nd Tuesday of each month. Also, we hope to rotate the venue around the Bay Area. Hadley's presentation will be on the Cal Berkeley campus. Exceptions

Good day R-listers, I'm working with a panel dataset, i've used many models , homogeneous (fixed effect, pooled ols and Driscoll and Kraay) heterogeneous (swamy random coefficients) and would like to do a post-estimation to select the model that best fit my regression. is there any method, command that may allow me to do this in R? Any hint will be highly appreciated Ama.

Hello, I am actually using ZFS under FreeBSD, but maybe someone over here can help me anyway. I''d like some advice if I still can rely on one of my ZFS pools: [user at host ~]$ sudo zpool clear zpool01 ... [user at host ~]$ sudo zpool scrub zpool01 ... [user at host ~]$ sudo zpool status -v zpool01 pool: zpool01 state: ONLINE status: One or more devices has experienced an

R, I want to get means and confidence limits on the original scale for the treatment effect after running a mixed model. The data are: response<-c(16,4,5,8,41,45,10,15,11,3,1,64,41,23,18,16,10,22,2,3)

DeaR all, I am using mob() for model based partitioning, with a dichotomous variable (participant's correct/incorrect response to a test item) regressed onto a continuous predictor related to a given property of the test item. Although this variable is continuous, the value of this variable for many items in this particular analysis is 0. The partitioning criterion is self-reported ability in

Dear useRs: I try to use mob from the party package (thanks Achim and Co.!) to model based recursive partition a data set. The model is a logistic regression specified with model=glinearModel and family=binomial(). Running mob results in a few warnings of the type: In glm.fit ... algorithm did not converge. As I speculate that this may be due to an insufficient number of iterations I am

Dear useRs: I successfully model-based partitioned several datasets through the use of mob from the party package (thanks Achim et al. once again !!!). At times, however, the partitioning leads to terminal nodes in which the parameter estimates of the model are not significant (although the split points and in general the proposed segmentation both seem reasonable). As I do not seem to be able

I'll be upgrading the SVN server on llvm.org this Friday from 9pm - whenever I am done. You will notice that all web and of course svn services will be down during this time. Thanks, Tanya