similar to: tournaments to dendrograms

Could someone advise me about how to react to the message: * checking R code for possible problems ... NOTE slm: no visible binding for global variable 'response' from R CMD check SparseM with * using R version 2.6.0 Under development (unstable) (2007-09-03 r42749) The offending code looks like this: "slm" <- function (formula, data, weights, na.action, method =

I'm trying to install the current R-devel on a G4 powerbook. I'm using ./configure --enable-R-shlib --with-blas='-framework vecLib' --with-lapack with rudjer: gcc -v Reading specs from /usr/libexec/gcc/darwin/ppc/3.1/specs Thread model: posix Apple Computer, Inc. GCC version 1175, based on gcc version 3.1 20020420 (prerelease) rudjer: g77 -v Reading specs from

Is there a painless way to find the names of all packages on CRAN that "Depend" on a specified package? url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820

I sent the message below to r-sig-mac yesterday, but having no reply I decided to explore a bit myself and found that editing: /Library/Frameworks/R.framework/Versions/2.3/Resources/share/make/ shlib.mk yzzy: diff shlib.mk shlib.mk~ 3c3 < include $(R_HOME)/etc/Makeconf --- > include $(R_HOME)/etc${R_ARCH}/Makeconf restored the functionality of R CMD INSTALL. Is this a known issue?

I'm having problems with environments and update() that I expect have a simple explanation. To illustrate, suppose I wanted to make a very primitive Tukey one-degree-of- freedom for nonadditivity test and naively wrote: nonadd <- function(formula){ f <- lm(formula) v <- f$fitted.values^2 g <- update(f, . ~ . + v) anova(f,g) } x <-

I discovered recently that the phrase "Oja median" produces no hits in Jonathan Baron's very valuable R search engine. I found this surprising since I've long regarded this idea as one of the more interesting notions in the multivariate robustness literature. To begin to remedy this oversight I wrote a bivariate version and then decided that writing a general p-variate version

Thierry, I have this: if (require(MatrixModels) && require(Matrix)) { X <- model.Matrix(Terms, m, contrasts, sparse = TRUE) in my function rqss() I've tried variants of requireNamespace too without success. If I understand properly model.Matrix is from MatrixModels but it calls sparse.model.matrix which is part of Matrix, and it is the latter function that I'm not

Greetings, I'm organizing summer econometrics lunch meetings to discuss thesis work. The first meeting will be this friday July 18 12-1pm in the conference room on the third floor of Wohlers. The first talk will be by Lingjie Ma Control Variate Estimation of Structural Quantile Regression Models url: www.econ.uiuc.edu/~roger/my.html Roger Koenker email rkoenker@uiuc.edu Department of

My apologies, the data can now be found at: url <- "http://www.econ.uiuc.edu/~roger/research/ebayes/velo.d" x <- scan(url,skip = 1) If I could get each of the histograms to mimic what is produced by hist(x, 100, freq = FALSE) I?ve experimented with xlim, ylim, without success so far... url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu

Hi Roger, As we know that The Oja median has (finite) breakdown point 2/n, i.e., is not robust in any reasonable sense, and is quite expensive to compute, so do we have some better methodology to compute multivariate median Rahul Agarwal Analyst Equities Quantitative Research UBS_ISC, Hyderabad On Net: 19 533 6363 [[alternative HTML version deleted]]

I have a pdf scan of several pages of data from a quite famous old paper by C.S. Pierce (1873). I would like (what else?) to convert it into an R dataframe. Somewhat to my surprise the pdf seems to already be in a character recognized form, since I can search for numerical strings and they are nicely found. Of course, as is usual with such tables there are also headings and column

Negative indexing is often handy, but I'm in need of an appropriate idiom for handling cases in which the index set can be null: x <- rnorm(5) a <- 1:5 s <- rep(FALSE,5) y <- x[-a[s]] # I'd like y == x but instead one has x[-a[s]] == x[a[s]] == numeric(0), which is rather # unfortunate -- so far the best I have come up with is: as <- ifelse(length(a[s]),-a[s],TRUE)

An extremely modest proposal: It would be nice if packages could have a FAQ and if faq(package.name) would produce this faq. And if, by default faq() FAQ() would produce the admirable R faq... Apologies in advance if there is already a mechanism like this, but help.search() didn't reveal anything. url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at

Dear All, I'm trying to track down a problem with my quantreg package reported by a user doing censored quantile regression. When he runs the test4.R file attached below (which reads the csv file also attached) on his windows machine he gets an error like this: > Error in dimnames(B) <- list(c("tau", dimnames(x)[[2]], "Qhat"), NULL) : > length of

Hi. I am aware of three different R packages for linear programming: glpk, linprog, lpSolve. From what I can tell, if there are N variables and M constraints, all these solvers require the full NxM constraint matrix. Some linear solvers I know of (not in R) have a sparse matrix input format. Are there any linear solvers in R that have a sparse matrix input format? (including the

What is the current state of the R-art for ordered probit models, and more esoterically is there any available R strategy for ordered cauchit models, i.e. ordered multinomial alternatives with a cauchy link function. MCMC is an option, obviously, but for a univariate latent variable model this seems to be overkill... standard mle methods should be preferable. (??) Googling reveals that spss

It being friday, I would like to call your attention to an innovative data analysis by Leslie Lamport available from: http://research.microsoft.com/users/lamport/pubs/hair.pdf I particularly liked the graphics. url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois

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Dear List, I would greatly appreciate help on the following matter: The RuleFit program of Professor Friedman uses partial dependence plots to explore the effect of an explanatory variable on the response variable, after accounting for the average effects of the other variables. The plot method [plot(summary(rq(y ~ x1 + x2, t=seq(.1,.9,.05))))] of Professor Koenker's quantreg program

I'm writing a new predict method and would like to be able to pass an argument called "se" via the "..." mechanism. However, predict has a "se.fit" argument that wants to interpret my specification of "se" as a partially matched version of se.fit. Surely there a standard treatment for this ailment, but I can't seem to find it. url: