similar to: Help: CallerID Name not being sent on outbound PRI trunk

My legacy PBX accepts CID number, but not name. My old PRI vendor never sent the name, so there was never an issue. I have wedged asterisk between the Legacy PBX and PSTN. PSTN - PRI - asterisk - PRI - Legacy. Any calls from asterisk (sip and iax extensions) which have callerID set, will not connect. The legacy PBX hangs up, but asterisk thinks that it is still ringing. I have added

We are trying to send caller ID NAME information over a Telus PRI in Alberta. The PRI tech says that he sees the NAME information, and for calls over the same network, that NAME info should be reaching the receiving station, but it is not. The technician was stumped. I suspect there's something specific that I need to do to make it work, since many PBXs can do this. The switch is a

Egad, not again with Broadvoice! Anyhow, I recently installed AAH and configured my TDM11B and got that and some SIP phones working. I still have some issues to work out, etc, but my current problem is Broadvoice. I have checked out all of the online resources, including the recent list exchange about the recent changes made by Broadvoice. However, the one thing I have found to be consitent in

Hello, I use nnet to do prediction for a continuous variable. after that, I calculate correlation coefficient between predicted value and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega

Hi! I'm running 1.1rc4 on a system and this happens occasionally: --8<-- mail.info; dovecot: auth(default): client in: AUTH 1 PLAIN service=imap lip=NN.NN.NN.NN rip=NNN.NN.NNN.NN lport=143 mail.info; dovecot: auth-worker(default): pam(XXXXXXXXXXXX,NNN.NN.NNN.NN): lookup service=imap kern.alert; kernel: grsec: From NN.NN.NN.NN: denied resource overstep by requesting

I have the following problem. I have an automatically generated named list with "stringified" names: a <- list("A"=..., "B"=..., "C"=..., ) then I want to refer to the elements of the list, stored as an vector of names: nn <- c("A", "B", "C"), so that I could get list elements like a$nn[1], a$nn[2], etc. Obviously it

Hello, (Apologies for length, wanted to get all the relevant detail in that I know of). I've been having a lot of trouble with some code for an inventory analysis problem I was doing, and finally came to the conclusion that it appears that choose() is returning incorrect values. Specifically: ------------- Browse[1]> nn [1] 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3

Group It's unlikely I'm trying this the best way, but I'm trying to create a data structure from elements like nNode = 2 nn = vector("list",nNode) nn[[1]] = list(Node = "1", Connect.up = c(NULL), Connect.down = c(2,3)) nn[[2]] = list(Node = "2", Connect.up = c(1), Connect.down = c(4,5)) .... #( and eventually many more nodes) NodeList =

Is this a bug, or have I misunderstood the proper use of lm? Thanks, Whit code: x <- rnorm(50) y <- matrix(as.logical(round(runif(100),0)),ncol=2) NROW(x)==NROW(y) lm(x~y) > x <- rnorm(50) > y <- matrix(as.logical(round(runif(100),0)),ncol=2) > NROW(x)==NROW(y) [1] TRUE > lm(x~y) Error in "[[<-.data.frame"(`*tmp*`, nn, value = c(2, 1, 2, 1, 1, 1, 2, :

Dear R-list, I try to transform a mathematica script to R. #######relevant part of the Mathematica script (* p_sv *) dd = NN (DsD - DD^2); lownum = NN (L-DD)^2; upnum = NN (H-DD)^2; low = lownum/(2s^2); up = upnum/(2s^2); psv = NIntegrate[1/(s^NN) Exp[-dd/(2s^2)] (Gamma[1/2,0,up] + Gamma[1/2,0,low]),{s,sL,sH}, MinRecursion->3]; PSV = psv/Sqrt[2NN]; Print["------------- Results

Folks, Updating values in a table is simple in SAS or SQL, but I've wracked my brain looking for an elegant solution in R to no avail thus far. Certainly this is a common need that's been solved in dozens of different ways. Given an initial dataframe nn and a smaller dataframe of updates uu, I'd like to replace the values in nn <- expand.grid('a'=1:4, 'b'=1:3)

Sat, 06 Dec 2014 07:19:29 +1300 from Andrew Bartlett <abartlet at samba.org>: >On Fri, 2014-12-05 at 11:50 +0300, ?????? wrote: >> Hi All >> >> Having problem to join Samba as BDC in existing domain >> >> PDC - w2003 >> >> Partition[DC=MKS,DC=lan,DC=net] objects[10114] linked_values[0] >> Refusing to replicate

> t(t(NN)/lambda) [,1] [,2] [,3] [1,] 0.5 0.6666667 0.75 [2,] 2.0 1.6666667 1.50 > R matrices are column-based. MATLAB matrices are row-based. > On Feb 27, 2024, at 14:54, Evan Cooch <evan.cooch at gmail.com> wrote: > > So, trying to convert a very long, somewhat technical bit of lin alg > MATLAB code to R. Most of it working, but raninto a stumbling block

I decided to do a direct comparison of transpose and sweep. library(microbenchmark) NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix lambda <- c(2, 3, 4) # Example vector colNN <- t(NN) microbenchmark( sweep = sweep(NN, 2, lambda, "/"), transpose = t(t(NN)/lambda), colNN = colNN/lambda ) Unit: nanoseconds expr min lq

Dear Sir: When I try to save large and very complex recursive objects with some components containing models (such as the output from arima or lm ), the resulting file sizes increase by 4 meg per save. example directory: amex 8 meg argentina 12 meg australia 16 meg ... Moreover, I am unable to read these file objects back into R. I note that readBin and writeBin

I have a conceptual problem (sort of). Maybe there's a simple solution, maybe not. First, let me explain the test case that goes ok. Let x be a (fixed) n-dimensional vector. I simulate a lot of linear models, y = m x + c + error, then I do a lot of regressions. As expected, the estimated values of m (let's call them m.bar) are distributed according to a Student's t distribution.

Hi, I have the following problem. It has two parts. 1. I need to calculate the stationary probabilities of a Markov chain, eg if the transition matrix is P, I need x such that xP = x in other words, the left eigenvectors of P which have an eigenvalue of one. Currently I am using eigen(t(P)) and then pick out the vectors I need. However, this seems to be an overkill (I only need a single

Why anything but sweep? The fundamental data type in Matlab is a matrix... they don't have vectors, they have Nx1 matrices and 1xM matrices. Vectors don't have any concept of "row" vs. "column". Straight division is always elementwise with recycling as needed, and matrices are really vectors in row-major order: 1 2 3 4 5 6 is really 1 4 2 5 3 6 and when you do

So, trying to convert a very long, somewhat technical bit of lin alg MATLAB code to R. Most of it working, but raninto a stumbling block that is probaably simple enough for someone to explain. Basically, trying to 'line up' MATLAB results from an element-wise division of a matrix by a vector with R output. Here is a simplified version of the MATLAB code I'm translating: NN = [1,

Hi all, I was trying to convert a data frame to a zoo object so I can use some time series functions like lag(). But it seems then everything became a factor, so I have to convert it back to numeric to run the correct regressions. Is there a way to avoid it? Here is an example: ############################# a <- data.frame(nn =as.character(c("a", "b", "c",