similar to: Aggregate

I need help with (hopefully) just one more thing. I have been fussing with this for quite some time and have decided just to give up and ask! I want to match a column in a matrix to a vector. I found a "which" command that I thought would be helpful as it does the following: > g=c(1,5,3,2,7) > which(g==5) [1] 2 As the above gave which placement in the g vector corresponded to

After loading the RODBC package version 1.1-7, Ctrl-C changes its behaviour and is quitting R and returning to the (unix-)command prompt on the solaris2.8 platform here. Here's what happened before and after loading RODBC > for (i in 1:10^5) rnorm(10) ^C > library(RODBC) > for (i in 1:10^5) rnorm(10) ^C bash-3.00$ platform sparc-sun-solaris2.8 arch

I am encountering a make error on an AIX 5.2 with R-2.3.0 and R-patched_2006-05-10 after successfully configuring them using gcc-4.1.0, gnu make, and the following configure options CC=/usr/local/bin/gcc F77=/usr/local/bin/gfortran CXX=/usr/local/bin/g++ MAIN_LDFLAGS=-Wl,-brtl SHLIB_LDFLAGS=-Wl,-G CFLAGS='-g -O' FFLAGS='-O' CXXFLAGS='-g -O' bash-3.00$ ./configure

Hello all, I was wondering if the following behaviour of margin.table in R 1.3.0 is normal. > mm <- data.frame(x=c(0,0,1), y=c(1,1,0), z=c(0,1,0)) > margin.table(mm,1) [1] 1 2 3 <0 rows> (or 0-length row.names) while using 'apply(x,margin,sum)' I get > apply(mm,1,sum) 1 2 3 1 2 1 which appears to be normal. Similar behaviour when margin=2. On the other hand, the

Using AIX 5.3 and gcc-4.2.1 for building R-2.7.1 with the following configure flags OBJECT_MODE=64 CC="gcc -maix64" CXX="g++ -maix64" F77="gfortran -maix64" FC="gfortran -maix64" CFLAGS="-g -O3" CXXFLAGS="-g -O3" FFLAGS="-g -O3" FCFLAGS="-g -O3" LDFLAGS="-L/$HOME/usr/local/lib/ppc64

I am trying to get R-2.2.1 to pass make check on an AIX 5.2 at work (I know R-2.2.1 is not the latest release, but I encountered make errors in my attempts to install either R-2.3.0 or the R-patched_2006-05-10 on the version of AIX I am on. I will post those errors in a separate posting from this.) So far, configure and make finish without error for R-2.2.1 using gnu make, gcc-4.1.0, and

Per the request to test the latest tarball referenced below, I have built R on AIX 5.3. There is a memory issue, please see 3) below. 1) Build with --enable-BLAS-shlib option. Builds and passes "make check". 2) GNU libiconv was installed; R configured *without* the --without- iconv option. Builds and passes "make check." 3) Memory issue: a)

With much thanks to Ei-ji Nakama, R 2.5.0 alpha supports building on AIX (at least AIX 5.2 on one system). Would anyone able to test this please get the latest tarball from http://cran.r-project.org/src/base-prerelease/R-latest.tar.gz and try installing (after reading the AIX notes in R-admin.html section C.9). In particular it would be very helpful to know if 1) --enable-BLAS-shlib works

I asked a question that might help me track down what changed between 2.3.1 that did build and the 2.4.0 version that will not build. Some of the undefined names the linker was complaining about looked like #define symbols that were not picked up by configure. The first thing I was hoping for was to find out if this problem looked familiar? Whether or not, I'm willing to try to work on

Good Morning, Is it possible to use the R program for a CFA with dichotomous data? Thank you, Kathleen Kathleen Kemp, M.A. Doctoral Clinical Psychology Student, Concentration: Forensic Psychology Drexel University Philadelphia, PA 19104 kk354@drexel.edu [[alternative HTML version deleted]]

Dear list members, How can I replace the nested for loops at then end of the script below with more efficient code? # Begin script__________________________________________________ # Dichotomous scores for 100 respondents on 3 items with # probabilities of a correct response = .6, .4, and .7, # respectively x1 <- rbinom(100,1,.6) x2 <- rbinom(100,1,.4) x3 <- rbinom(100,1,.7) #

Dear R users, I have a large individual-level dataset (~700,000 records) which I am performing a conditional logistic regression on. Key variables include the dichotomous outcome, dichotomous exposure, and the stratum to which each person belongs. Using this individual-level dataset I can successfully use clogit to create the model I want. However reading this large .csv file into R and running

Hi there, Am I correct to believe that tetrachoric correlation is a special case of polychoric correlation when there are only two levels to the ordered factor? Thus it should be okay to use hetcor from the polycor package to build a matrix of correlations for binary variables? If this is true, how can one estimate 95% confidence intervals for the correlations? My guess would be mat =

List: Thank you for the replies to my post yesterday. Gabor and Phil also gave useful replies on how to improve the function by relying on mapply rather than the explicit for loop. In general, I try and use the family of apply functions rather than the looping constructs such as for, while etc as a matter of practice. However, it seems the mapply function in this case is slower (in terms of CPU

I want to test whether the proportional odds assumption for an ordered regression is met. The UCLA website points out that there is no mathematical way to test the proportional odds assumption (http://www.ats.ucla.edu/stat//R/dae/ologit.htm), and use graphical inspection ("We were unable to locate a facility in R to perform any of the tests commonly used to test the parallel slopes

Hi Sorry for the rather long message. I am trying to use the cfa command in the lavaan package to run a CFA however I am unsure over a couple of issues. I have @25 dichotomous variables, 300 observations and an EFA on a training dataset suggests a 3 factor model. After defining the model I use the command fit.dat <- cfa(model.1, data=my.dat, std.lv = T, estimator="WLSMV",

Hello All, I have a 131072x132 matrix for which I need to compute a regular euclidean distance matrix, which I then need to transform and run agnes() on this transformed matrix. I am having trouble computing the distance matrix as it is fairly large and I am sure I have gone over the max. The specific error I am getting is: Error in vector("double", length) : negative length vectors

Dear community I'm pretty new to R and I'm trying to do a Point-baserial correlation for a nominal dichotomous variable with a interval scaled variable. It works fine, but the output just shows me the correlation and nothing else (p-Value would be important). I tried it with the following codes: - biseral.cor() - cor.biseral() - I also tried a polyserial() I've found on this

Hello R-User! I appologise in advance if this should also go into statistics but I am presently puzzled. I have a data.frame (about 300 rows and about 80 variables) and my variables are dichotomous factors, continuous (numerical) and ordered factors. I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm())

Hello list, Probably a newbie question but couldn''t find the answer in the archives. I am using the login_engine Plugin to implement the login functionality. I have a JournalEntry model that interacts with the journal_entries table. I would like to link the journal entries to the user who entered it. Essentially, it is a one to many relationship between the model User(from