similar to: new package 'bvls', update of 'nnls'

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,

Dear All, A short-term (approx. 6-month) postdoctoral or scientific programmer position is available in a computational sciences project in Amsterdam. The title is dependent on experience. The starting date should be before the end of 2008, and applicants must be a citizen of a member state of the European Union. The ideal applicant would: o be an experienced R programmer o have experience in

Dear All, A new task view "ChemPhys" on chemometrics and computational physics is available on CRAN (http://cran.r-project.org/web/views/ChemPhys.html). It describes packages and functions that are of use in modeling chemical/physical systems. Suggestions and comments regarding this task view are welcome. If you think a new category, package or function should be added, please mail.

Hi Is there an R package that solves linear least squares with upper and lower bounds on the variables. Something like the Parker and Stark algorithm written in Fortran. thanks

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

To add to the wish-list for "convolve": For modeling processes that decay exponentially in time, e.g., fluorescence, it is desirable to have a function that convolves an arbitrary vector with an exponential using an iterative method. In the TIMP package (which won't be on CRAN till R 2.5.0 is official, but is for now at www.nat.vu.nl/~kate/TIMP) we implemented this special-purpose

I'm trying to get significance of coefficients as for lm() but I news help. Inviato da iPad [[alternative HTML version deleted]]

Hi all, Dear Dr. Wheeler, I am trying to use the lmPerm package to perform multiple regression on microarray data with certain empirical variables associated with treatments of the experiment. In order the circumvent the very conservative multiple test corrections such as Bonferroni and BH, I try to use permutated probabilities to assess associations. In addition to mu previous posting I

Hi, I'm trying to find the corresponding Fortran77 subroutines for R function pt(). I tried some Fortran77 subroutines to compute the t distribution function. But none of them are as good as R function pt(). Does anyone can give me some information about it? Thank you very much! Tianyue

Dear All, Probably a very basic question, but can't seem to work my way around it. I want to which row has the maximum value. But what if the row names do not correspond with the row numbers. In the example below, you'll see that the max of example is row 4, but the name of row 4 is "9". How do I get R to return "9" as value, instead of 4. example <-

Thank you Brian Ripley, Gardar Johannesson, and Marcel Wolbers for your prompt and friendly help! I will share any further learnings as I move through these suggestions. -Bob Abugov Brian Ripley wrote: I just use optim() on the sum of squares with non-negativity constraints. That did not exist in 1999. Gardar Johannesson wrote: You can always just use the quadratic programing library in R

Try as I might I can't seem to get LLVM to bulid using clang/clang++. No matter what I do it insists on using /usr/bin/cc and /usr/bin/c++ which are gcc. Am I missing something obvious? I vaguely remember some document describing a stage1 compiler built by your old toolchain and a stage2 compiler but I can't find the steps to do that any more. $ CC=/usr/local/bin/clang

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

or add acl_xattr:ignore system acl = yes to your share. more info man smb.conf .. Gr. Louis >-----Oorspronkelijk bericht----- >Van: J.Morillo at educationetformation.fr >[mailto:samba-bounces at lists.samba.org] Namens MORILLO Jordi >Verzonden: vrijdag 5 juni 2015 15:21 >Aan: samba at lists.samba.org >Onderwerp: Re: [Samba] [Bug or Limitation] Folder sharing

Hi, Given i have this share : [j.snow] Path = /home/j.snow Share and ntfs permission : j.snow user Now I add another folder share inside the first one : [a.stark] Path = /home/j.snow/a.stark Share and ntfs permission : a.stark user /home/j.snow/a.stark has now parent inherit permission (j.snow) AND a.stark user a.stark can't access to her share ! if I add a.stark NTFS access to [j.snow]

On 19/09/2018 3:52 PM, Philip B. Stark wrote: > Hi Duncan-- > > Nice simulation! > > The absolute difference in probabilities is small, but the maximum > relative difference grows from something negligible to almost 2 as m > approaches 2**31. > > Because the L_1 distance between the uniform distribution on {1, ..., m} > and what you actually get is large, there

Hm, that bug has been closed as resolved but I still see the problem: $ clang --version clang version 3.8.0 (trunk 250848) (llvm/trunk 250846) Target: x86_64-unknown-linux-gnu Thread model: posix InstalledDir: /usr/local/bin configure:4042: ./conftest FATAL: Code 0x5615faea43f0 is out of application range. Non-PIE build? FATAL: MemorySanitizer can not mmap the shadow memory. FATAL: Make sure to

For a well-tested C algorithm, based on my reading of Lemire, the unbiased "algorithm 3" in https://arxiv.org/abs/1805.10941 is part already of the C standard library in OpenBSD and macOS (as arc4random_uniform), and in the GNU standard library. Lemire also provides C++ code in the appendix of his piece for both this and the faster "nearly divisionless" algorithm. It would be