similar to: Summary: non-negative least squares

I got this wired behaviour of the attr() function using R-1.6.1 on both linux redhat 7.3 (i386) and Solaris 8 (Sparc): > tmp <- list(id=1) > > attr(tmp,"n.ch") <- 2 > attr(tmp,"n") <- 1 > tmp $id [1] 1 attr(,"n.ch") [1] 2 attr(,"n") [1] 1 > > attributes(tmp) $names [1] "id" $n.ch [1] 2 $n [1] 1 >

This might be because I didn't get it right, but; I thought R would release memory back to the system as (big) objects get removed? Here is my platform (with 1Gb of RAM): platform sparc-sun-solaris2.8 arch sparc os solaris2.8 system sparc, solaris2.8 status major 1 minor 3.1 year 2001 month 08 day 31 language R A little example: Start a new section of R, with

I'm trying to find a good way of attaching a list within a function such that the attached variables (the list's members) precede the global environment (.GlobalEnv) in the search list. Here is a non-working example using attach(), which hopefully explains better what I'm trying to do: > foo <- function(x=0, input=list(a=10)) { + attach(input) + on.exit(detach(input)) +

I have this 'odd' problem; I need to let R pause, for a given time, before starting next iteration in a loop. I'm using the following to do this task, but feel a little bit guilty because I'm using as much CPU time as I can get while pausing: while(keepGoing) { t.end <- proc.time()[3] + 5 ## the time this loop should end at [block of R commands] while(proc.time()[3]

This is something that I have not seen in earlier beta versions of 1.6.0: . . . ts.plot text html latex example ts.union text html latex example tsSmooth text html latex tsdiag text html latex example R_LIBS= ../../../bin/R CMD INSTALL ERROR: no packages

I have been trying out R-1.6.0 tarballs (2002-9-10 and 2002-9-17) on: arch sparc os solaris2.8 system sparc, solaris2.8 status beta major 1 minor 6.0 year 2002 month 09 day 17 language R As you see form above, R-1.6.0 compiles fine and works. However, when I "make fullcheck" I get the following error: running code in 'tools-Ex.R' ... OK

This is a little success story about the benefits of changing the defaults in config.site when I was building R-1.4.0 for Solaris (on a Sun Sparc that I'm currently using). For previous versions of R, I had just used the default config.site and not given it any thought. Since the Sun machine that I'm using is not getting any faster, I decided I would give config.site a look when building

The question was: > I have this 'odd' problem; I need to let R pause, for a given time, before > starting next iteration in a loop. I'm using the following to do this > task, but feel a little bit guilty because I'm using as much CPU time as I > can get while pausing: > > while(keepGoing) { > t.end <- proc.time()[3] + 5 ## the time this loop should end

Im trying to do regressions with constraints that the weights are all >=0 and sum(weights) = 1. I've read the archive and have set the problem up with solve.QP and just the non-negativity constraints along the lines of: y as the data vector X as the design matrix D <- t(X) %*% X d <- t(t(y) %*% X) A <- diag(ncol(X)) b <- rep(0,ncol(X)) fit <-

I have been playing around with sparse matrices in the Matrix package, in particularly with the Cholesky factorization of matrices of class dsCMatrix. And BTW, what a fantastic package. My problem is that I have to carry out repeated Cholesky factorization of a spares symmetric matrices, say Q_1, Q_2, ...,Q_n, where the Q's have the same non-zero pattern. I know in this case one does

A new package 'nnls' is now available on CRAN. The package provides an R interface to the Lawson-Hanson NNLS algorithm for non-negative least squares that solves the least squares problem A x = b with the constraint x >= 0. The Lawson-Hanson NNLS algorithm was published in Lawson CL, Hanson RJ (1974). Solving Least Squares Problems. Prentice Hall, Englewood Cliffs, NJ. Lawson CL,

A new package 'nnls' is now available on CRAN. The package provides an R interface to the Lawson-Hanson NNLS algorithm for non-negative least squares that solves the least squares problem A x = b with the constraint x >= 0. The Lawson-Hanson NNLS algorithm was published in Lawson CL, Hanson RJ (1974). Solving Least Squares Problems. Prentice Hall, Englewood Cliffs, NJ. Lawson CL,

---------- Forwarded message ---------- From: <r-help-bounces@r-project.org> Date: Mon, May 11, 2009 at 10:24 PM Subject: The results of your email commands To: das.moumita.online@gmail.com The results of your email command are provided below. Attached is your original message. - Results: Ignoring non-text/plain MIME parts - Unprocessed: What is the function for partial

Hello R experts, I have two questions related to the nnls library (http://www.inside-r.org/packages/cran/nnls), and more broadly to linear regression with positive coefficients. Sample code is below the Qs. Q1: Regular regression (with lm) gives me the significance of each variable. How do I get variable significance with nnls? If there's no ready function, any easy way to manually derive

A new package 'bvls' is available on CRAN. The package provides an R interface to the Stark-Parker algorithm for bounded-variable least squares (BVLS) that solves A x = b with the constraint l <= x <= u under least squares criteria, where l,x,u \in R^n, b \in R^m and A is an m \times n matrix. The Stark-Parker BVLS algorithm was published in Stark PB, Parker RL (1995).

A new package 'bvls' is available on CRAN. The package provides an R interface to the Stark-Parker algorithm for bounded-variable least squares (BVLS) that solves A x = b with the constraint l <= x <= u under least squares criteria, where l,x,u \in R^n, b \in R^m and A is an m \times n matrix. The Stark-Parker BVLS algorithm was published in Stark PB, Parker RL (1995).

I am trying to run the following function (a hierarchical bayes linear model) and receive the error in solve.default. The function was originally written for an older version of SPlus. Can anyone give me some insights into where the problem is? Thanks R 2.4.1 on MAC OSX 2mb ram Mark Grant markg at uic.edu > attach(Aspirin.frame) > hblm(Diff ~ 1, s = SE) Error in solve.default(R, rinv)

I'm trying to execute some commands on my ups, but I keep getting ERR ACCESS-DENIED upscmd -l sinus Instant commands supported on UPS [sinus]: beeper.toggle - Toggle the UPS beeper load.off - Turn off the load immediately load.on - Turn on the load immediately shutdown.return - Turn off the load and return when power is back shutdown.stayoff - Turn off the load and remain off shutdown.stop -

Hi all, I am trying to do an inversion of electromagnetic data with non-negative least squares method (Tikhonov regularisation) and have got it programmed in S-Plus. However I am trying to move all my scripts from S-Plus to R. Is there an equivalent to nnls.fit in R? I think this can be done with pcls? Right? S-Plus script: A, L and data are matrices, lambda is a vector of possible lambda

Hi, recently I saw but did not pay too much attention to a question that concerned regression with positive coefficients. In Splus, thereis the nnls() function that can be used if I am not wrong, but what about R ? Now I have the same problem: doing a logistic regression under constraint that coefs are non negative. What can I do with R? is there a (weighted) nnls() counterpart available? Thanks