similar to: Handling large dataset & dataframe

Here's a skeletal example. Embellish as needed: p <- 5 n <- 300 set.seed(1) dat <- cbind(rnorm(n), matrix(runif(n * p), n, p)) write.table(dat, file="c:/temp/big.txt", row=FALSE, col=FALSE) xtx <- matrix(0, p + 1, p + 1) xty <- numeric(p + 1) f <- file("c:/temp/big.txt", open="r") for (i in 1:3) { x <- matrix(scan(f, nlines=100), 100,

I'm having difficulty with an environmental issue: I have an additive model fitting function with a typical call that looks like this: require(quantreg) n <- 100 x <- runif(n,0,10) y <- sin(x) + rnorm(n)/5 d <- data.frame(x,y) lam <- 2 f <- rqss(y ~ qss(x, lambda = lam), data = d) this is fine when invoked as is; x and y are found in d, and lam is found the

> ... reports that the fortran names of all the registered fortran functions are ?undocumented objects?... Those symbols should not be exported. In quantreg v5.33, NAMESPACE has 'exportPattern(".")'. Maybe it is a good time to remove that and export explicitly the symbols that are meant for export. Georgi Boshnakov ------------------------------ Message: 6 Date: Fri, 28

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

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

On 28/06/2019 6:27 a.m., Koenker, Roger W wrote: > Thanks, I was just coming to that conclusion and beginning to look for a way to make a list of > exportable objects. After library(quantreg), ls("package:quantreg") will list all the names you currently export. So cat(ls("package:quantreg"), sep = ", ") will print the list in a form suitable for including

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

In principle a good idea, but I'm not sure the whereabouts of Catherine Loader are known at this point. Last peeps from her on the net seem to be about a decade old. .pd > On 18 May 2020, at 10:31 , Abby Spurdle <spurdle.a at gmail.com> wrote: > > This has come up before. > > Here's the last time: > https://stat.ethz.ch/pipermail/r-devel/2019-March/077478.html

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

FWIW the link from ?dbinom to the Loader paper on Binomials is broken but the paper seems to be available here: https://octave.1599824.n4.nabble.com/attachment/3829107/0/loader2000Fast.pdf Roger Koenker r.koenker at ucl.ac.uk<mailto:r.koenker at ucl.ac.uk> Honorary Professor of Economics Department of Economics, UCL Emeritus Professor of Economics and Statistics, UIUC [[alternative

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 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 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?

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

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 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

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

Hi, I am trying to use quantile regression to perform weighted-comparisons of the median across groups. This works most of the time, however I am seeing some odd output in summary(rq()): Call: rq(formula = sand ~ method, tau = 0.5, data = x, weights = area_fraction) Coefficients: Value Std. Error t value Pr(>|t|) (Intercept) 45.44262 3.64706 12.46007

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)