similar to: integer overflow

I'm trying to resolve a small problem that has arisen from introducing a NAMESPACE for the package SparseM. Prior to the namespace I had a class "matrix.diag.csr" that consisted of diagonal sparse matrices. It was defined to have the same attributes as the matrix.csr class and setAs was used to define how to coerce integers and vectors into this form:

In the last few days I've received couple of messages pointing out that our SparseM package fails to install on the patched version of 1.7.0. Laurent Gaultier kindly suggested that replacing: setGeneric("as.matrix.csr") by setGeneric("as.matrix.csr", function(x, nrow, ncol, eps) standardGeneric("as.matrix.csr")) was sufficient to fix the problem.

I'd like to mention that there is a new quantile regression package "nprq" on CRAN for additive nonparametric quantile regression estimation. Models are structured similarly to the gss package of Gu and the mgcv package of Wood. Formulae like y ~ qss(z1) + qss(z2) + X are interpreted as a partially linear model in the covariates of X, with nonparametric components defined as

I would like to add a class to the SparseM package. I have a class "matrix.csr" that describes a matrix in compressed sparse row format, now I would like a class matrix.diag.csr that describes such objects when they happen to be diagonal. The idea is that matrix.diag.csr objects should behave (later in life) exactly like matrix.csr objects, the distinction is only needed in order to

Dear all, I'm training an SVM with default settings on a matrix csr (SparseM package). I realized that if I train the SVM with the (hopefully) equivalent matrix (Matrix package) representation, the returned models and predictions sometimes differ. I expected both representations of the same data to lead to the same results though. It could be that it is a scaling problem, because unscaled

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've installed R-devel R Under development (unstable) (2014-07-09 r66111) Platform: x86_64-apple-darwin13.1.0 (64-bit) and am trying to resolve some problems that I am seeing with my SparseM package. In prior versions I explicitly had: setGeneric("image", function(x, ...) standardGeneric("image")) and then used setMethod to define a method for the class matrix.csr but

I'm hoping that someone with deeper insight into S4 than I, that is to say virtually everyone reading this list, could help resolve the following problem in SparseM. We have setGeneric("backsolve", function(r, x, k = NULL, upper.tri = NULL, transpose = NULL, twice = TRUE, ...) standardGeneric("backsolve"), useAsDefault= function(r, 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?

----- Forwarded Message ---- From: Nnamdi <nnamdii at yahoo.com> To: roger koenker <rkoenker at uiuc.edu> Sent: Friday, April 18, 2008 1:08:58 PM Subject: Re: [R] efficiently replacing values in a matrix I tried the sparse matrix implementation, still there are issues: a <- matrix(nrow=10000,ncol=10000) > a.csr <- as.matrix.csr(a) Error in if (nnz == 0) { : missing value

Hi, I have just installed R 2.4.0 and when I try to load SpareseM, I get the following error message library(SparseM) Package SparseM (0.71) loaded. To cite, see citation("SparseM") Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'SparseM' methods specified for export, but none defined: as.matrix.csr, as.matrix.csc,

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

> On Mar 26, 2015, at 8:50 AM, Martyn Plummer <plummerM at iarc.fr> wrote: > > On Wed, 2015-03-25 at 15:12 -0500, Roger Koenker wrote: >> Thierry, >> >> I have this: >> >> if (require(MatrixModels) && require(Matrix)) { >> X <- model.Matrix(Terms, m, contrasts, sparse = TRUE) > > You have this in the current release, which

Johannes, You can minimize an model expression by just putting the ~ on the left and everything else on the righthand side, but I don't think that this is really what you want. In the NLS expression this would ignore the jacobian of the transformation from errors to response, and in nlrq there is the same problem, however you can adjust for the jacobian by rescaling by the geometric mean of

For a paper on "Reproducible Econometric Research," Achim Zeileis and I would be interested in hearing from anyone with (positive) experience and/or suggestions about GUI-based data analysis from a reproducibility perspective. We omitted coverage of this topic in an initial draft on the well-known principle: if you can't say something nice, say nothing at all,"

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

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

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)

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: