similar to: typo or stale info in qr man

> Date: Wed, 30 Jun 1999 11:12:24 +0200 (MET DST) > From: Torsten Hothorn <hothorn at amadeus.statistik.uni-dortmund.de> > > yesterday I had a little shock using qr (or lm). having a matrix > > X <- cbind(1,diag(3)) > y <- 1:3 > > the qr.coef returns one NA (because X is singular). So I computed the > Moore-Penrose inverse of X (just from the

Hello. I am trying to invert a matrix, and I am finding that I can get different answers depending on whether I set LAPACK true or false using "qr". I had understood that LAPACK is, in general more robust and faster than LINPACK, so I am confused as to why I am getting what seems to be invalid answers. The matrix is ostensibly the Hessian for a function I am optimizing. I want to get

Le 22/01/2018 ? 17:40, Keith O'Hara a ?crit?: > This behavior is noted in the qr documentation, no? > > rank - the rank of x as computed by the decomposition(*): always full rank in the LAPACK case. For a me a "full rank matrix" is a matrix the rank of which is indeed min(nrow(A), ncol(A)) but here the meaning of "always is full rank" is somewhat confusing. Does it

The following snippet suggests that there is either a bug in qr(,LAPACK=T), or some bug in my understanding. Note that the detected rank is correct (= 2) using the default LINPACK qr, but incorrect (=3) using LAPACK. This is running on Linux Redhat 9.0, using the lapack library that comes with the Redhat distribution. I'm running R 1.7.1 compiled from the source. If the bug is in my

Dear R Developers, I should have had the Design library running in R by now but have kept putting off changing some calls to LINPACK routines to use those builtin to R. Specifically I call dqrsl1 and dqr. Would it be an easy task to put those in the next release of R? If not I'll finally bite the bullet and get back into reading LINPACK documentation (which I have but haven't examined

Might it be possible to tighten the definition of "is.qr". I noticed that after I mistakenly typed example(lm) # make lm object named lm.D9 qr.Q(lm.D9) which exhausted the heap memory and produced two warning messages. As an object of class "lm" has a "qr" component, "is.qr" failed to detect that "lm.D9" was not a "qr" object. The

Le 23/01/2018 ? 08:47, Martin Maechler a ?crit?: >>>>>> Serguei Sokol <sokol at insa-toulouse.fr> >>>>>> on Mon, 22 Jan 2018 17:57:47 +0100 writes: > > Le 22/01/2018 ? 17:40, Keith O'Hara a ?crit?: > >> This behavior is noted in the qr documentation, no? > >> > >> rank - the rank of x as

I'm feeling kinda stupid right now, but I'm actually having problems compiling R-0.62.3 on a Red Hat 5.1 Linux system. I'd be happy if someone could point out for me where to look to fix the problem. I've included the output from the compiling below. Thanks for any help. Fredrik make -f Makefile.2nd all make[1]: Entering directory `/home/fredrigl/R-0.62.3' Building R cd

Dear Sirs, I am trying to compile R v1.2.1 under Digital Unix 4.0D. The configure-script runs without any problems but during 'make' I receive the following error-message: [......] g77 -mieee -g -O2 -c dtrco.f -o dtrco.o g77 -mieee -g -O2 -c dtrsl.f -o dtrsl.o g77 -mieee -g -O2 -c eigen.f -o eigen.o g77 -mieee -g -O2 -c lminfl.f -o lminfl.o ar cr libappl.a Rsock.o approx.o bakslv.o

I have been struggling to find some informaation on what lm exactly does. I know it uses the QR decomp. However, I was recently faced with a somewhat badly scaled matrix and summary(lm) said Coefficients: ( 4 not defined because of singularities) does anyone know how lm chooses these 4 coef. is it forward building of the model --> drop last when qr sends a non full rank design matrix? My

Hi Everyone, I have modified my version of R-1.4.1 to include choleski with pivoting (like in Splus). I thought R-core might consider including this in the next version of R, so I give below the steps required to facilitate this. 1. Copied Linpack routine "dchdc.f" into src/appl 2. Inserted line F77_SUBROUTINE(dchdc) in src/appl/ROUTINES 3. Inserted "dchdc.f" into

Hello, This morning I downloaded, unzipped, and compiled the latest version of R for unix, in my HOME/APPLICATIONS directory. My current unix machine is a sparc-sun-solaris2.9, running SunOS 5.9. Here are the last few lines of the output following ./configure: R is now configured for sparc-sun-solaris2.9 Source directory: . Installation directory: /usr/local C compiler:

2017-06-22 19:49 GMT+02:00 Uwe Ligges <ligges at statistik.tu-dortmund.de>: > On 22.06.2017 17:11, Bernd Funovits wrote: >> >> Hello, >> >> I experienced some unexpected behaviour while determining the rank of matrices (sometimes 1x1 matrices): >> base::qr(matrix(1e-20))$rank returns 1 (incorrect) >> base::qr(diag(c(1, 1e-20)))$rank returns 2

I want to speed up computations (involving matrices) by writing some C-code to be loaded. In the C-code, I need to invert matrices etc. As I've understood the "writing R extensions" doc, I can use use #include <R_ext/Linpack.h> in my .c-file and get access to linpack's facilities within my C-code. Is that correct? If so, can anyone point me to examples on how this is

I suggest adding a 'pivot' argument to qr.R, to obtain columns in the same order as the original x, so that a <- qr(x) qr.Q(a) %*% qr.R(a, pivot=TRUE) returns x. -------------------------------------------------- # File src/library/base/R/qr.R qr.R <- function(qr, complete = FALSE, pivot = FALSE) { # Args: # qr: a QR decomposition, produced by qr() # complete:

2017-06-22 20:31 GMT+02:00 Uwe Ligges <ligges at statistik.tu-dortmund.de>: > > > On 22.06.2017 20:09, I?aki ?car wrote: >> >> 2017-06-22 19:49 GMT+02:00 Uwe Ligges <ligges at statistik.tu-dortmund.de>: >>> >>> On 22.06.2017 17:11, Bernd Funovits wrote: >>>> >>>> >>>> Hello, >>>> >>>> I

Recent sensible changes to the dynload mechanism have made an old problem resurface: how should we deal with packages which contain Fortran code and may need to be linked against additional libraries such as -lf2c? The current consensus is that extra Fortran libraries maybe needed are handled via the make variable FLIBS, and that `-lf2c' or `-lg2c' are added by default if g77 is used.

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 <- >

G'day all, I had a look at the GLM code of R (1.4.1) and I believe that there are problems with the function "glm.fit" that may bite in rare circumstances. Note, I have no data set with which I ran into trouble. This report is solely based on having a look at the code. Below I append a listing of the glm.fit function as produced by my system. I have added line numbers so that I

With this example set.seed(123) A <- matrix(runif(40), nrow = 8) y <- 1:nrow(A) A.laqr <- qr(A, LAPACK=TRUE) both qr.qy(A.laqr,y) and qr.qty(A.laqr,y) give the respective error messages Error in qr.qy(A.laqr, y) : 'b' must be a numeric matrix Error in qr.qty(A.laqr, y) : 'b' must be a numeric matrix However when Lapack is not used as in A.liqr <- qr(A,