similar to: Managing output

Hi, I want to create variable names from within my code, but can't find any documentation for this. An example is probably the best way to illustrate. I am reading data in from a file, doing a bunch of stuff, and want to generate variables with my output. (I could make a "list of lists" and name all the elements, but I really want separate variables.) ################# #This is

Hello, I was just assigned to perform a cost effectiveness study in healthcare. We are studying the cost effectiveness of a proposed diagnostic vs. current screening procedures. One of the team members suggest a commercial software package called "TreeAge Pro". Looking at the description, it appears to be a nice GUI to some very simple models that could be easily constructed in R.

Hello, I have a time series object (xts) that I iterate over in a loop. Works fine. My challenge is that I want to be able to reference other entries in the series by math. i.e. For today's observation, what were the last 5 observations? If indexed numerically, it is trivial, but I can figure out how to do this with dates. This is slightly more difficult as there may not be an

I have a bunch of data sets that were created for the libsvm tool. They are in "colon separated sparse format". i.e. 1 5:1 27:3 345:10 Is a row with the label of "1" and only has values in columns 5, 27, and 345. I want to read these into a data.frame in R. Is there a simple way to do this? -- Noah Silverman, M.S. UCLA Department of Statistics 8117 Math Sciences

Hello, I need to design a fairly simple front-end for someone to use an R script system that I've built. My thought was to just use the text based menus available in the base R package, perhaps in some kind of loop. How have other people done this? Any "best practices" that you can recommend? Thanks! -- Noah Silverman UCLA Department of Statistics 8117 Math Sciences Building

Hi, Our discussions about 64 bit R has led me to another thought. I have a nice dual core 3.0 chip inside my Linux Box (Running Fedora 11.) Is there a version of R that would take advantage of BOTH cores?? (Watching my system performance meter now is interesting, Running R will hold a single core at 100% perfectly, but the other core sites idle.) Thanks! -- Noah

Hi, I'm looking at the "cocktail party" classic problem. I can see how to use ICA to separate the components. But, How do I then create new wav files of the separated sounds so that they can be played? Thanks -- Noah Silverman UCLA Department of Statistics 8208 Math Sciences Building Los Angeles, CA 90095 [[alternative HTML version deleted]]

I'm running a long MCMC chain that is generating samples for 22 variables. I have each run of the chain as a row in a matrix. So: Chain[,1] is the column with all the samples for variable one. Chain[,2] is the column with all the samples for variable 2, etc. I'd like to fit all 22 on a single page to print a nice summary. It is OK if the graphs are small, I just need to show the

We have two small business that run out of our office. One business has 3 phone lines, and the other has only one. In a perfect world, Asterisk would indicate WHICH line (or group) the outsider caller called, so that we would know which way to answer the phone. The incoming calls would go through a voice mail menu first - different for each company. (Press one for sales, two for

Hello, I need to calculate a moving average and an exponentially weighted moving average over a fairly large data set (500K rows). Doing this in a for loop works nicely, but is slow. ewma <- data$col[1] N <- dim(data)[1] for(i in 2:N){ data$ewma <- alpha * data$ewma[i-1] + (1-alpha) * data$value[i] } Since the moving average "accumulates" as we move through the data,

Hi, The answers to my previous question about nominal variables has lead me to a more important question. What is the "best practice" way to feed nominal variable to an SVM. For example: color = ("red, "blue", "green") I could translate that into an index so I wind up with color= (1,2,3) But my concern is that the SVM will now think that the values are

Hi, I have a data.frame that I need to scale. I've been using the scale function and it works nicely. Some of the libraries I'm testing won't accept negative values for data, so I need to find a way to scale the data from 0 to 1 Any ideas? Thans!

Hello, I'm attempting to build a package using R 2.15.0 on OS X I am getting a generic failure when performing a cran type check on the package. Even with a very simple test package, it still fails int he same place. Example: In R: rm(list=ls()) foo <- function(x){print(x)} package.skeleton(name="foo") Then, at the command line: R CMD build foo R CMD check --as-cran

Hi, I need a bit of guidance with the sapply function. I've read the help page, but am still a bit unsure how to use it. I have a large data frame with about 100 columns and 30,000 rows. One of the columns is "group" of which there are about 2,000 distinct "groups". I want to normalize (sum to 1) one of my variables per-group. Normally, I would just write a huge

Hi, I have a CSV file that is formatted well, except that the last line is a "summary" not is CSV format. Toy example: label_1, label_2, label_3 1,2,3 3,2,4 2,3,4 Total Rows: 3 When I try to import this into R with: d <- read.table("foo.csv", header=T, sep=",") It fails to import properly because of the last line. Currently, I have a shell script that strips

Hi, Next challenge today. I have a script that I call within R: source("foo.R") When it finishes, I get the dreaded output: "There were 50 or more warnings (use warnings() to see the first 50)" So, I type warnings() and get a nice list. (Same error repeatedly, so probably something I'm using in a loop.) The difficult part is I have no idea *where* the warning is

Hi, Looking at a large data set with many factors. I would like to expand each factor variable into multiple new variables for each level. (0,1) coding. My first though was just to code a big nasty loop, to take each level and cbind a column onto my data set. But, that seems painful. There must be a better way. Is there an "easy" way to do this in R? (Note, I don't want to

Hi, I have a very large data set (aprox. 100,000 rows.) The data comes from around 10,000 "groups" with about 10 entered per group. The values are in one column, the group ID is an integer in the second column. I want to normalize the values by group: for(g in unique(groups){ x[group==g] / sum(x[group==g]) } This works find in a loop, but is slow. Is there a faster way to do

Unfortunately, some data I need to work with was delivered in a rather messy Excel file. I want to import into R and clean up some things so that I can do my analysis. Pulling in a CSV from Excel is the easy part. My current challenge is dealing with some text mixed in the values. i.e. 118 5.7 <2.0 3.7 Since this column in Excel has a "<2.0" value, then R reads the

Dean - > if you are having these troubles and everyone keeps advising you to use > asterisk@home why aren't you doing this? Not to be rude, but I believe you are the only one who suggested he use asterisk@home. asterisk@home is a great (actually stupendous) product for those that want to have a PBX with a GUI up and running within a few minutes. It does not, however, force users