similar to: wishlist: function mlh.mlm to test multivariate linear hypotheses of the form: LBT'=0 (PR#8680)

Hi all I am having some issues with a gs 100 phone. It is on the same network as my * server. There is no firewall. In extentions.conf exten => 5,1,Answer exten => 5,2,MusicOnHold(default) When I dial 5 from the sip phone -- Executing Answer("SIP/mlh-2e75", "") in new stack -- Executing MusicOnHold("SIP/mlh-2e75", "default") in new stack

I just checkout the cvs code for asterisk...... when I use my grandstream phone (that worked on the old code that was about 2 months old) I do not hear anything at all... I get this error: Sep 27 23:20:27 WARNING[1142127920]: File chan_sip.c, Line 444 (retrans_pkt): Maximum retries exceeded on call 0765c89e-9d67-3c0a-b9b9-2e7f3cd1d9ef@192.168.50.248 for seqno 58430 (Response) here is my

I just got a grandstream SIP phone Here is my sip.conf for the phone [mlh] type=friend insecure=yes username=mlh secret=mlh host=dynamic canreinvite=no The phone as the default config on it. If I use the phone to call a Zap interface (a tdm card) the voice sounds all choppy. If I use the phone to call a x100p card, it does not dial what I dial (no DTMF) I don't know

Dear R-help list, I have a problem storing results from a bootstrap loop. What I doing is creating an empty matrix before the loop, then run the loop. Before the end of the loop I have a command line which defines which results inside the loop will have to go in the empty matrix. Here is the code I am using: eigen.values<-rep(NA,boots) #storage file for eigen values (1 for simulation)

Hello Does anybody know how one can compute d largest eigenvalues/eigenvectors in R, like in MATLAB eigs function ? eigen function computes all eigenvectors/eigenvalues, and they are slightly different than those generated by matlab eigs. Thanks in advance -- View this message in context: http://www.nabble.com/matlab-eigs-function-in-R-tp17619641p17619641.html Sent from the R help mailing list

Hi listers, I want to make lattice plots xyplots with the indication of legends inside each panel with only the points and the lines actually ploted inside each given panel according to the group(ing) factor. The code below shows what I have achieved so far and I hope will make clear what I want to have. It seems to me that my solution is a very "dirty hack" and there certainly is

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file:

Hi, I was wondering if anyone knew of an implementation of a function similar to "eigs" in Matlab (full description here: http://www.mathworks.com/access/helpdesk/help/techdoc/ref/eigs.html). This function differs from the standard "eigen" in that it computes a *few* eigenvectors for cases in which your matrix is very large and/or you don't need all the eigenvectors.

Hi @llvm, I had to comment out template<> struct DFSetTraits<LoopBlocksTraversal> { static void finishPostorder(BasicBlock *BB, LoopBlocksTraversal& LBT) { LBT.finishPostorder(BB); } }; in LoopIterator.h in order to get the latest llvm compiling. I guess it is going to be removed anyway. Best regards Olaf Krzikalla

Dear all, I want to compute the eigenvalues of a complex matrix for some statistics. Comparing it to its matlab/octave sibling, I don't get the same eigenvalues in R computing it from the exact same matrix. In R, I used eigen() and arpack() that give different eigenvalues. In matlab/octave I used eig() and eigs() that give out the same eigenvalues but different to the R ones. For real

hi I'm puzzled as to the relation between the REML score computed by gam and the formula (4) on p.4 here: http://opus.bath.ac.uk/22707/1/Wood_JRSSB_2011_73_1_3.pdf I'm ok with this for poisson, or for quasipoisson when phi=1. However, when phi differs from 1, I'm stuck. #simulate some data library(mgcv) set.seed(1) x1<-runif(500) x2<-rnorm(500)

Hi R-users I'm trying to do multivariate analysis of variance of a experiment with 3 treatments, 2 variables and 5 replicates. The procedure adopted in SAS is as follow, but I'm having difficulty in to implement the contrasts for comparison of all treatments in R. I have already read manuals and other materials about manova in R, but nothing about specific contrasts were found in them,

Hi Greg, For quasi families I've used extended quasi-likelihood (see Mccullagh and Nelder, Generalized Linear Models 2nd ed, section 9.6) in place of the likelihood/quasi-likelihood in the expression for the (RE)ML score. I hadn't realised that this was possible before the paper was published. best, Simon ps. sorry for slow reply, the original message slipped through my filter for

Dear R-devel'ers Below is an outline for a set of routines to improve support for multivariate linear models and "classical" repeated measurements analysis. Nothing has been coded yet, so everything is subject to change as loose ideas get confronted by the harsh realities of programming. Comments are welcome. They might even influence the implementation... -pd General

Thank you for reading. I am trying to get sphericity values, and I understood I need to use mlm, but how do I implement a nested within subject design in mlm? I already read the R newsletter, fox chapter appendix, EZanova, and whatever I could find online. My original ANOVA anova(aov(resp ~ sucrose*citral, random =~1 | subject, data = p12bl, subset = exps==1)) Or anova(aov(resp ~

Signed-off-by: Simon COURTOIS <scourtois at linagora.com> --- src/app/controllers/vm_controller.rb | 16 ++++++++++++++ src/app/views/vm/edit_vmpool.rhtml | 36 ++++++++++++++++++++++++++++++++ src/app/views/vm/show.rhtml | 3 ++ src/public/images/icon_vmpool_11px.png | Bin 0 -> 542 bytes 4 files changed, 55 insertions(+), 0 deletions(-) create mode 100644

Signed-off-by: Simon COURTOIS <scourtois at linagora.com> --- src/app/controllers/vm_controller.rb | 16 +++++++++++++ src/app/views/vm/edit_vmpool.rhtml | 39 ++++++++++++++++++++++++++++++++ src/app/views/vm/show.rhtml | 3 ++ src/public/images/icon_vmpool_11px.png | Bin 0 -> 542 bytes 4 files changed, 58 insertions(+), 0 deletions(-) create mode 100644

I'm coming from the AMOS world and am wondering if there is a simple way to do multiple hypothesis testing in the manner of BIC analyses in AMOS using the sem package in R. I've read the documentation, but don't see anything in there except for basic BIC scores. Perhaps someone has devised a simple way to compare the relative likelihood of all possible path-fittings within a

We recently installed Asterisk 1.4.2 Tried to make calls using the Originate command (Asterisk Manager Interface) All of the calls have zero billsec in the CDR. Stumbled upon this: http://bugs.digium.com/view.php?id=8680 so I guess the fix is not yet in 1.4.2. Is this fixed in 1.4.3/1.4.4? -------------- next part -------------- An HTML attachment was scrubbed... URL:

predict.mlm fails with the error: Object "X" not found. CAUSE: looking at the predict.mlm function, we have: x <- model.matrix(object, newdata) two lines later, we have: pred <- X[, piv, drop=FALSE] %*% object$coefficients[piv,] SOLUTION(?): change the case of one of the x's, since it seems like what is meant in the second line is lowercase x... platform: