similar to: I think simple R question

I'm sorry to bother this list so much But I haven't programmed in A while and I'm struggling. I have a vector in R of 1's and -1's And I want to use a streak of size Y To predict that the same value will Be next. So, suppose Y = 3. Then, if there is a streak of three ones in a row, then I will predict that the next value is a 1. But, if there is a streak of 3 -1's in

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 =

Does anyone have (good) experience converting tables of tournament results into dendrogram-like graphics? Tables, for example, like this: read.table(url("http://www.econ.uiuc.edu/~roger/research/ncaa/NCAA.d")) Any pointers appreciated. RK url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558

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'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

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'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

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?

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

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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 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)

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

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

Hi, I have a dataset consisting of 350,000 rows and 266 columns. Out of 266 columns 250 are dummy variable columns. I am trying to read this data set into R dataframe object but unable to do it due to memory size limitations (object size created is too large to handle in R). Is there a way to handle such a large dataset in R. My PC has 1GB of RAM, and 55 GB harddisk space running

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

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