similar to: na.rm default

I'm wondering if there's a way to set which periodic-announce file is played from my dialplan, much like setting the monitor-filename. Something like this: exten => s,n, Set(PERIODIC_ANNOUNCE=foo) This would be a great feature if it doesn't already exist. Or perhaps there's a better way to do this. Thanks for your time. -- Regards, Robert Broyles

I saw some of the heat about the $20 bounty earlier. So I don't want to put a low bounty out. Quote me a bounty, and I'll see if I can get it approved by management. :-) I'm in need of getting this bug fixed. Bug has all of the details, but basically 1.4.22 broke it all. I've waited as long as I can - hoping the bug would 'resolve itself' - but now I'm putting a

So I'm using the READ() application within an IVR, and having a strange issue, and wondering if anyone else has had this problem. When calling from an outside line, and entering the digits during the read() part of my dialplan, it's accepting some of the digits twice, though it's only keyed in once. When testing the dialplan internally, it accepts only the digits that I key in.

Is there a way to override the queue wrapup time on the fly? I would like to allow a longer wrapup time for my agents, but if they are already done with closing up the call ticket, I would like them to be able to dial an extension or something to override the wrapup. Is there a way to do that? -- Regards, Robert Broyles

I'm using R-2.6.2 on Fedora Linux 9. I've been experimenting with plotmath. I wish it were easier to combine expressions in plotmath with values from the R program itself. There are two parameters in the following example, the mean "mymean" and standard deviation "mystd". I am able to use bquote to write elements into the graph title like mu = mymean and R will

Dear R-users, Is there a function in R that classifies data in more than 2 groups using logistic regression/classification? I want to compare the c-indices of earlier research (lrm, binary response variables) with new c-indices obtained from 'multiple' (more response variables) logistic regression. Best regards, Stephanie Delalieux Department Biosystems M?-BIORES Group of Geomatics

Dear All, I have a database of 200 observations named myD. In the dataframe there are a column named code (with codes varying from 1 to 77), a column named "prevalence" with some quantitative measurements are given and an column named Pr_mean, with no values. I would like to set a cycle to compute the average of prevalence values for each different code and store the averages under the

Hello, I have a general formatting question. I have two columns of data: ColA <- c("m", "m", "m", "m") ColB<- c("d","d","d","d") And I would like to reorder them into a new column that looks like this: ColC<-

Hello List, My question is an elementary one. I have run a fuzzy kmeans cluster using FANNY to group freshwater fish assemblages. I then went in the field to validate that classification and have retrieved new assemblage data for a new suite of streams. Therefore I would like to use Predict to determine how well the original clustering fits the new data. However I have not figured out a

Full_Name: Stephanie MAHEVAS Version: 2.4.1 OS: Windows NT Submission from: (NULL) (134.246.55.50) the two following instructions provide a synthax error : if ( 5 > 4 ) cat("ok1") else cat("ok2") and if ( 5 > 4 ){ cat("ok1")} else cat("ok2") whereas these ones don't if ( 5 > 4 ) cat("ok1") else cat("ok2") and if (

Hi, this is a made-up example. Function "myfun" returns two arguments. Can "apply" be used so that "myfun" is called only once? Thanks Serguei mat<-matrix(runif(50),nrow=10,ncol=5) myfun<-function(x) { mymean<-mean(x) mysd<-sd(x) return(mymean,mysd) } out1<-t(apply(mat,1,function(x) myfun(x)$mymean)) out2<-t(apply(mat,1,function(x)

Hi all, may i know is it possible to plot a graph by first letter? for example: Name: Age: Angel 20 Amelia 20 Bernard 19 Stephanie 20 Vanessa 22 Angeline 23 Camel 21 If I want to plot the name started with letter 'A' and their Angel,

Hi all, I have two very large samples of data (10000+ data points) and would like to perform normality tests on it. I know that p < .05 means that a data set is considered as not normal with any of the two tests. I am also aware that large samples tend to lead more likely to normal results (Andy Field, 2005). I have a few questions to ensure that I am using them right. 1) The Shapiro-Wilk

We love our Digium phones and DPMA - but we really need it to work on our Realtime Platform. Otherwise we lose all the cool features and they are just standard SIP phones. Anyone working on a solution for this? Or anyone from Digium see this on the roadmap?

Hi Everyone - Here is a draft of the first of two "pages" that I will submit to Wikipedia. The first page is a general network virtualization page. From this page, I will contribute a subpage on the Crossbow projects. These two articles are the first of a number of online articles on Crossbow that I''ll be creating on behalf of the Crossbow iteam. The article uses

Dear R users, My set-up: OS=Windows XP, R-2.9.2, Rtools210 I faced the follwing problem with the package compilation: There is no "/inst" or "/etc" subdirectory in the package-zip-file. And the content of the "/etc" subdirectory is lost, too. I tried a simplified "test" package. The "test" package has the following structure (see also attachement:

Hi, I have been trying to use the function cochran.test from the Outliers package to test for homogeneity of variance. This works well except when I use transformed data. Would anyone have an idea why it doesn't work and how I could do the cochran test on transformed data? Thanks, Stephanie >library(outliers) > set.seed(1234) > x=rnorm(100) >

Hello, I am using tapply to pull out data by the day of week and then perform functions (e.g. mean). I would like to have the number of values used for the calcuation for the functions, sorted by each day of week. A number of entries in any given column are NAs. I have tried the following code and simple variants with no luck. for (i in 1:length(a[1,])){ x<-tapply(a[,i],a[,1],mean,

I have a dataframe ("mydf") that contains "differences of means". I wish to test whether these differences are significantly different from zero. Below, I calculate the t-statistic for each column. What is a "good" method to calculate/look-up the p-value for each column? mydf=data.frame(a=c(1,-22,3,-4),b=c(5,-6,-7,9)) mymean=mean(mydf) mysd=sd(mydf)

In my own package, I want to use the default S3 method of the generic function lrtest() from the lmtest package. Since I need only one function from lmtest, I tried to use importFrom in my NAMESPACE: importFrom(lmtest, lrtest) However, this fails R CMD check in the examples: Error in UseMethod("lrtest") : no applicable method for 'lrtest' applied to an object of class