similar to: random text added to names (bug with 2.10.0?)

I have 2 ISDN BRI boxes, each with 4 spans, where the first one is configured as CPE, the second one as NET(so I don't need real lines for developing and testing). Once in a while I do see the following libpri error messages simultaneously on both boxes: PRI Span: 1 TEI=0 MDL-ERROR (A): Got supervisory frame with F=1 in state 7(Multi-frame established) PRI Span: 2 TEI=0 MDL-ERROR (A): Got

I have some more investigation to do on this, but I wanted to see if anyone here had any insight into the issue I've run into. The hardware is a HP DL360 G6 with a TE420 gen 5 4-port T1 PRI card. It is one of several systems that have been running without issue since 2010/2011. They have all been running CentOS 4 32-bit with Zaptel 1.4.12.1 (with patch for gen 5 card), libpri 1.2.8 and

Hello, I have a data frame > mdl.summary est.coef std.err t.stat intercept 0.0011625517 0.0002671437 4.351784 aa -0.0813727439 0.0163727943 -4.969997 dummy1 -0.0002534873 0.0001204000 -2.105376 dummy2 -0.0007784864 0.0001437537 -5.415417 bb -0.0002856727

Hi, I seem to be having a problem adding the following two raster objects together - one is a rasterLayer, the other is a rasterBrick. The extent, resolution, and origin are the same, so according to my understand it should work. The objects look like so: > obs.clim class : RasterLayer dimensions : 60, 200, 12000 (nrow, ncol, ncell) resolution : 0.5, 0.5 (x, y) extent : -70,

In article <CAHZ_z=w5DMg93gShtC93kuC+fnmraPgV46BS956U5BQXVgyhxg at mail.gmail.com>, Matt Fredrickson <creslin at digium.com> wrote: > On Tue, Apr 3, 2018 at 5:44 AM, Tony Mountifield <tony at softins.co.uk> wrote: > > I have some more investigation to do on this, but I wanted to see if anyone > > here had any insight into the issue I've run into. > > >

Hello, I have successfully installed MDL ISIS Draw 2.5 (a program used in chemistry) under Wine (0.9.12 in Debian). Now, I need to install an addon (AutoNom2000, which is used to give IUPAC names of compounds) for this program. (This addon requires Windows 2000/XP; Wine was configured to "mimic" Windows 98 by default). When I try to run its installer, I get the following:

hello, I am trying to use predict.lm to make point forecasts based on a model with continuous and categorical independent variables I have no problems fitting the model using lm, but when I try to use predict to make point predictions. it reverts back to the original dataframe and gives me the point predictions for the fitted data rather than for the new data, I imagine that I am missing

Hi all, Last night I went to replace an Asterisk 1.4 + mISDN + b410p box with Asterisk 1.6.2 and DAHDI BRI - to no avail. I had two servers so copied network setting etc from the working one, moved the card across, ran dahdi_genconf etc and it didn't work. Here's the console output with notices disabled: lucas*CLI> pri intense debug span 1 Enabled debugging on span 1 [Dec 16

Hi All, I've a BT Versatility PBX that I want to connect to my asterisk 11.9.0 box via BRI port in NT mode but actually I wasn't able to get it working. I've another standalone PBX, it's a Panasonic model, which works fine connected to the same port. The BT connected to a UK BT BRI line works quite fine after roughly a minute once connected. The PBX can be seen at

I have a variable which is roughly age categories in decades. In the original data, it came in coded: > str(xxx) 'data.frame': 58271 obs. of 29 variables: $ issuecat : Factor w/ 5 levels "0 - 39","40 - 49",..: 1 1 1 1... snip I then defined issuecat as ordered: > xxx$issuecat<-as.ordered(xxx$issuecat) When I include issuecat in a glm model, the result

Could someone point me in the right direction for the following issue: A function is defined as follows: tfun <- function(dat) { fmla <- as.formula("y~x+z") dat2 <- dat mdl <- lm(fmla,dat2) mdl <- step(mdl) } Then the following code dat <- data.frame(x=1:10,z=1:10,y=(1:10)^2+10*(1:10)) tfun(dat) generates the output Start: AIC= 43.67

Dear R-users, I have a problem with randomForest{outlier}. After running the following code ( that produces a silly data set and builds a model with randomForest ): ####################### library(randomForest) set.seed(0) ## build data set X <- rbind( matrix( runif(n=400,min=-1,max=1), ncol = 10 ) , rep(1,times= 10 ) ) Y <- matrix( nrow = nrow(X), ncol = 1) for( i in (1:nrow(X))){

Hi all - I'm stumped by the following mdl <- glm(resp ~ . , data = df, family=binomial, offset = ofst) WORKS yhat <- predict(mdl) WORKS yhat <- predict(mdl,newdata = df) FAILS Error in drop(X[, piv, drop = FALSE] %*% beta[piv]) : subscript out of bounds I've tried without offset, quoting binomial. The offset variable ofst IS in df. Previous postings indicate possible

Some chemicals have concentrations at or below the method detection limit (MDL; 'less-thans') of 0.005 mg/L. When I look at the data frame that is how the concentration is displayed. But, when I ask for a summary() of that data frame column only 0 is displayed. How can I adjust the number of digits displayed by functions such as summary()? Rich

Hey, I'm looking for a function which provides a supervised Fayyad & Irani discretization (MDL). I've already found RWeka which has such a function. But is there anything else? I'd prefer to use sth lighter in my own package. Regards, Peter

Hi, may be somewon has a working solution and information on that: I installed the most recent mysql community on a server and do get a lot of "errno: 24 - Too many open files". There are suggestions to increase the open_files_limit, change/add that to /etc/security/limits.conf and modify the systemd script by hand. Depending on how you start mysql (restart, or at systemboot time

Ask a simple question : I svn checkout compiler-rt in llvm/project. And I compile llvm through cmake. How can I make for all those testing files? make test? - mudongliang 2015-09-02 0:58 GMT+08:00 Kostya Serebryany <kcc at google.com>: > Take a look at > > clang.llvm.org/docs/ControlFlowIntegrityDesign.html > clang.llvm.org/docs/ControlFlowIntegrity.html > > And the

Hi, I have the following code from Splus that I'd like to migrate to R. So far, the only problem is the arima.filt function. This function allows me to filter an existing time-series through a previously estimated arima model, and obtain the residuals for further use. Here's the Splus code: # x is the estimation time series, new.infl is a timeseries that contains new information # a.mle

Dear R-helpers: I am interested in discretization methods for numerical attributes, as they are reported in the 'machine learning' community. For example, the work of Fayyad & Irani (IJCAI-93), Kononenko, entropy-based approaches, MDL principle, the C4.5 approach, etc. I am especially interested in those methods that take a factor as goal target into account for discretizing

Hi, I am trying to fit a smoothing model where there are three dimensions over which I can smooth (x,y,z). I expect interactions between some, or all, of these terms, and so I have set up my model as mdl <- gam(PA ~ s(x) + s(y) + s(z) + te(x,y) + te(x,z) + te(y,z) + te(x,y,z),...) I have recently read about the ti(), "tensor product interaction smoother", which takes care of these