similar to: testInstalledBasic / testInstalledPackages

Hello all, I've developed a prototype package called PopCon (short for popularity contest), a package for tracking the popularity of R and its packages. I'd like this work to be similar in spirit to the Debian package popularity-contest: http://popcon.debian.org/. Once Popcon is loaded, it captures two kinds of information from the user and stores it into a cache: the names of the

(I posted this to the R-devel list yesterday, but I thought others on this list would be interested, so sorry for those who get it twice.) Hello all, I've developed a prototype package called PopCon (short for popularity contest), a package for tracking the popularity of R and its packages. I'd like this work to be similar in spirit to the Debian package popularity-contest:

I mean the `numeric_version` object not a numeric (double/int). Basically to protect me from myself I'd prefer not to have to remember to wrap `getNamespaceVersion()` with `as.package_version()`. I suspect a grep of CRAN may highlight others who are erroneously comparing character objects rather than a comparison between a `numeric_version` object and a character. Tim On 17/10/2024

On 17/10/2024 13:42, Tim Taylor wrote: > I mean the `numeric_version` object not a numeric (double/int). > Basically to protect me from myself I'd prefer not to have to remember > to wrap `getNamespaceVersion()` with `as.package_version()`. > > I suspect a grep of CRAN may highlight others who are erroneously > comparing character objects rather than a comparison between

Can anyone explain what I'm missing here? max(pp1 <- package_version(c("0.99999911.3","1.0.4","1.0.5"))) ## [1] ?1.0.4? max(pp2 <- package_version(c("1.0.3","1.0.4","1.0.5"))) ## [1] ?1.0.5? I've looked at ?package_version , to no avail. Since max() goes to .Primitive("max") I'm having trouble figuring out

Dear all, I am working on modifying the R working matrix to commodate some other correlations that not included in the package. I am having problem to locate where the R matrix are defined for regular matrices, i.e. independence, exchangeable, AR and unstructure. it might have something within .C("Cgee",but don't understand it well enough to know. Can you anyone help? /*gee source

On 17 October 2024 at 12:38, Tim Taylor wrote: | Would R-Core be receptive to having getNamespaceVersion() return a | numeric_version object instead of a named character? Is this good enough? What's your actual issue a 'numeric' would address? > as.package_version(getNamespaceVersion("base")) < "4.5.0" [1] TRUE > >

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

Full_Name: Ravi Varadhan Version: 2.8.1 OS: Windows Submission from: (NULL) (162.129.251.19) Inverting a matrix with solve(), but using LAPACK=TRUE, gives erroneous results: Here is an example: hilbert <- function(n) { i <- 1:n; 1 / outer(i - 1, i, "+") } h5 <- hilbert(5) hinv1 <- solve(qr(h5)) hinv2 <- solve(qr(h5, LAPACK=TRUE)) all.equal(hinv1, hinv2) #

I know that it has been discussed in the past, but I wanted to ask to revisit the idea of exporting is.formula <- function(x) inherits(x, "formula") from 'stats', parallel to is.data.frame() in 'base', given how widely formulae are used these days in conjunction with data frames, even outside of model fitting functions (e.g., for split-apply). One could argue

rvaradhan at jhmi.edu wrote: > Full_Name: Ravi Varadhan > Version: 2.8.1 > OS: Windows > Submission from: (NULL) (162.129.251.19) > > > Inverting a matrix with solve(), but using LAPACK=TRUE, gives erroneous > results: Thanks, but there seems to be a much easier fix. Inside coef.qr, we have coef[qr$pivot, ] <- .Call("qr_coef_real", qr, y, PACKAGE =

Hi All, Can someone tell me if solve function shown below for my version of R is proper or not? I am using R 2.7.2 .Wherever i have used this function ,i got results which were different from the expected results as computed using SPSS. Description of this function says:-- Solve a System of EquationsDescription This generic function solves the equation a %*% x = b for x, where b can be either

Hi All, I have millions of regression lines to fit. So I am looking for the most efficient approach in R. Details: I have a large desing matrix X. The dimension is n by p. Each time when fitting the model, select rows from this matrix X and form a new design matrix, called X_current. There is another binary matrix M, with dim m by n, and each row is a 1*n vector. It helps to determin X_current.

Two friend reported me a problem, which I can't solve: (I run R-1.0.0, Debian Linux) They hava a function "corr.matrix" (see end of mail), and when they create a 173x173 matrix with this function V <- corr.matrix(0.3, n=173) V1 <- qr.solve(V) reports: Error in qr(a, tol = tol) : NA/NaN/Inf in foreign function call (arg 1) For n < 173, qr.solve returns the correct

Hi all I'm getting a NaN returned on using dffits, as explained below. To me, there seems no obvious (or non-obvious reason for that matter) reason why a NaN appears. Before I start digging further, can anyone see why dffits might be failing? Is there a problem with the data? Consider: # Load data dep <-

With R-2.12.2 on Linux: > z <- data.frame(Version=package_version(c("0.1")), row.names=c("pkgA")) > all.equal(z, z) # expect TRUE Error: evaluation nested too deeply: infinite recursion / options(expressions=)? > traceback() ... lots of lines in a 3-cycle ... 6: all.equal.list(target, current, ...) 5: all.equal.default(target[[i]], current[[i]],

Refiling this. The actual fix was slightly more complicated. Will soon be committed to R-Patched (aka 2.9.1 beta). -p rvaradhan at jhmi.edu wrote: > Full_Name: Ravi Varadhan > Version: 2.8.1 > OS: Windows > Submission from: (NULL) (162.129.251.19) >=20 >=20 > Inverting a matrix with solve(), but using LAPACK=3DTRUE, gives erroneo= us > results: Thanks, but there seems

Full_Name: Yves Rosseel Version: 2.2.1 OS: Submission from: (NULL) (157.193.116.152) The code below sketches a possible implementation of a function 'mlh.mlm' which I think would be a good complement to the 'anova.mlm' function in the stats package. It tests a single linear hypothesis of the form H_0: LBT'= 0 where B is the matrix of regression coefficients; L is a matrix

Hi, all. I want to write some functions like glm() so i studied it. In glm.fit(), it calls a fortran subroutine named "dqrfit" to compute least squares solutions to the system x * b = y To learn how "dqrfit" works, I just follow how glm() calls "dqrfit" by my own example, my codes are given below: > qr <- >

Hi, I am running R 2.13.0 on a Windows 7 machine. I ran the script: testInstalledBasic('devel') and received the following warning message: running tests of consistency of as/is.* creating ?isas-tests.R? running code in ?isas-tests.R? comparing ?isas-tests.Rout? to ?isas-tests.Rout.save? ...running tests of random deviate generation -- fails occasionally running code in