similar to: Multinomial logistic regression under R and Stata

Dear all I am running R 1.4.1 on a Linux box. I have tried to label data points in a 3-d scatterplot, but without much success. What I did was as follows: > scatterplot3d(x, y, z) > identify(x, y, z, row.names(Data)) When I tried to click on/near the data points, I either receive this msg: warning: no point with 0.25 inches, or some numbers in Data, not the row names, come up on the

Hello, For a long time, I have been creating eps files from R using the following command: dev.copy2eps(file="my.eps") This has worked very well. But recently, the compositor of a journal is complaining that "The eps files would be useable except that they have not converted the type to outlines" Sorry for being vague, but I have no idea what this compositor is talking

Hello List, I would like to orthonormalize vectors contained in a matrix X taking into account row weights (matrix diagonal D). ie, I want to obtain Z=XA with t(Z)%*%D%*%Z=diag(1) I can do the Gram-Schmidt orthogonalization with subsequent weighted regressions. I know that in the case of uniform weights, qr can do the trick. I wonder if there is a way to do it in the case of non uniform

man for `qr` says that the function uses LINPACK's DQRDC, while it in fact uses DQRDC2. ``` The QR decomposition of the matrix as computed by LINPACK or LAPACK. The components in the returned value correspond directly to the values returned by DQRDC/DGEQP3/ZGEQP3 ```

Hi, I have eight vectors that I would like to orthogonalize preferably using R. The vectors are of considerable length, however due to their nature I know they satisfy the conditions needed to apply the Gram-Schmidt algorithm. Before I embark on some R coding, I wanted to check that there is no facility / function already around that computes the orthogonalized set of vectors? I have performed

Dear expeRts, I have run some simulations under R 2.15.1 on a Mac, and I have rerun a sample of them under R 3.0.1 on Windows (and also for comparison under R2.14.1 on Windows). For most cases, I get exactly the same results in all three runs. However, for those cases that depend on principal components computed with prcomp, where the particular choice of the orthogonalization is arbitrary

Dear expeRts, I have run some simulations under R 2.15.1 on a Mac, and I have rerun a sample of them under R 3.0.1 on Windows (and also for comparison under R2.14.1 on Windows). For most cases, I get exactly the same results in all three runs. However, for those cases that depend on principal components computed with prcomp, where the particular choice of the orthogonalization is arbitrary

Dear all R users, Can anyone tell me to calculate Eigen value of any real symmetric matrix which algorithm R uses? Is it Jacobi method ? If not is it possible to get explicit algorithm for calculating it? Thanks and regards, Arun [[alternative HTML version deleted]]

While I am not a novice when it comes to statistics, this will be the first time I have used R, apart from some intial play. I have normally written my own code for statistical analysis in C++ or fortran, for a number of reasons (in part contingent on what the boss was willing to pay for), and having been programming for a long time, there is no need to spare me the programming details.

Hi, Is there a function in any of R-packages that can produce and plot the impulse response function for any model.. Thank you Ahmad Abu Hammour -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

Hey, R-listers, I have a question about determining the orthogonal basis vectors. In the d-dimensinonal space, if I already know the first r orthogonal basis vectors, should I be able to determine the remaining d-r orthognal basis vectors automatically? Or the answer is not unique? Thanks for your attention. Fred

Suppose one wanted to consider random variables X_1,...X_n and from each subtract off the piece which is correlated with the previous variables in the list. i.e. make new variables Z_i so that Z_1=X_1 and Z_i=X_i-cov(X_i,Z_1)Z_1/var(Z_1)-...- cov(X_i,Z__{i-1})Z__{i-1}/var(Z_{i-1}) I have code to do this but I keep getting a "non-conformable array" error in the line with the covariance.

Hello, I have had numerous issues with PJSIP outbound calling in Asterisk 13.1.0 and SIP.US SIP trunk. My Asterisk server is on EC2 and I have opened up the appropriate ports. The SIP clients can be anywhere on the Internet, including behind NATs. I am able to get to my Asterisk server's internal extensions via the DID (and appropriate dialplans) but I am not able to make outbound calls to

I am looking at a new project involving time series analysis. I know I can complete the tasks involving VARMA using either dse or mAr (and I think there are a couple others that might serve). However, there is one task that I am not sure of the best way to proceed. A simple example illustrates what I am after. If you think of a simple ballistic problem, with a vector describing current

A correction. You either need to open the plotting device prior to the simulation that includes your plotting commands and close it after the simulation or have the name change dynamically in your simulation so that the runs go in separate files. An example of the first method would be postscript(file="/where/to/put/file/filename.ps") ## your simulation commands dev.off() for the

I've just released the latest R-Forge versions of heplots 0.9-3 and candisc 0.5-18 to CRAN. They should appear there within a day or two. == heplots The heplots package provides functions for visualizing hypothesis tests in multivariate linear models (MANOVA, multivariate multiple regression, MANCOVA, etc.). They represent sums-of-squares-and-products matrices for linear hypotheses and for

On 5/2/07, r-help-request@stat.math.ethz.ch < r-help-request@stat.math.ethz.ch> wrote: > > Send R-help mailing list submissions to > r-help@stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit > https://stat.ethz.ch/mailman/listinfo/r-help > or, via email, send a message with subject or body 'help' to >