search for: isotone

Well, I could argue that it's not *completely* OT since my question is motivated by an enquiry that I received in respect of a CRAN package "Iso" that I wrote and maintain. The question is this: Given observations y_1, ..., y_n, what is the solution to the problem: minimise \sum_{i=1}^n (y_i - y_i^*)^2 with respect to y_1^*, ..., y_n^* subject to the "isotonic"

Hi, Has anyone written code for isotonic regression on ordered rectangular grids? Nathan Nathan Leon Pace, MD, MStat University of Utah Salt Lake City, UT 84132 Office: 801.581.6393 Fax: 801.581.4367 Cell: 801.558.3987 Pager: 801.291.9019 Home: 801.467.2925 [[alternative text/enriched version deleted]]

dear R-help: one of my students is struggling to test an ordered alternative hypothesis on a set of groups (e.g., mu_a <= mu_b <= mu_c). There has been some literature on this topic -- a lot of this goes back to Bartholomew (1961); Gaines and Rice (see refs below) are the ones who've popularized it in the ecology community. The topic is closely related to isotonic regression, but

Dear R-users Do you know of an easy way in R of performing "isotonic (unimodal)" regression ala BBBB, Barlow, Bartolomew, Brenner and Brunk. best regards Helgi -- Helgi Tomasson FAX: 354-552-6806 University of Iceland PHONE:354-525-4571 Faculty of Economics and Business Administration email:helgito at

Hi All, I need some help with the package 'isotone'? I have a big matrix (long) and I want to apply 'lsSolver' possibly with 'activeSet' to each row of the matrix. The plan is to use function 'apply', I tried several ways, but didn't work. Not sure if the FUN is activeSet or lsSolver. If I use the loop, then it wor...

Before re-inventing the wheel I would like to ask: does anyone know about an optimizer in R which can reliably identify which value of X (Xopt) leads to Y (Yopt) closest to Ytarget in Y <- MonotoneStepFun(X) optionally with the restriction that Yopt <= Ytarget (at least if any Y <= Ytarget, otherwise any Yopt > Ytarget would be the preferred answer) If none is known, I will write

Dear Sir/Madam: this is shuangge Ma, graduate student in UW-Madison statistics department. I have a computational question. I have a function f(x,y). I want to find the y(x) that maximize f(x,y) under the constraint y(x) is a non-decreasing step function. Is there any R package or algorithm I can use for this purpose? thanks a lot for your time and help, Sincerely, Shuangge Ma

Dear All, A method for the estimation is univariate unimodal densities (with unknown mode) is described in "Statistical Inference under Order Restrictions" by Barlow et al.. Would anyone know whether there is an R-implementation (preferably with reference) for the estimation of univariate discrete unimodal densities (with unknown mode)? Thanks in advance for your help. Kind

Hi all, I'm looking for smooth monotone estimation packages, preferably using splines. I downloaded the 'cobs' package and intend to use it, but since it offers only quadratic splines based on L1 minimization, I'd like to compare its performance to that of a more 'mainstream' cubic-spline, L2-norm minimizing spline. Preferably a smoothing spline. Does anyone know of such

Hi, I'm trying to find an implementation of monotonic regression in R and I haven't been able to find anything that's really related to this. isoMDS in the MASS package uses monotonic regression, however, I was wondering if there is any standalone function for monotonic regression? Basically what I'm trying to do is implement monotonic regression where I can see not just the

This seems to be a recurrent topic, but I don't remember hearing a definitive answer. I also apologies for cross-posting. Say I have a numerical response variable and a bunch of multi-level factors I want to use for modeling. I don't expect factor interaction to be important so there will be no interactions in the model. All this would be a perfect job for ANOVA except for one additional

...rogrammed in C and/or FORTRAN (sometimes using existing routines), and the loop over variables will be parallelized using OpenMP or Grand Central Dispatch. For ordinal variables this requires some alternative quadratic programming routines to be linked in (which could then also become part of the isotone package). In addition the basic homals code will have object (individual) weights (minor addition) and the prehom routines (from the jacobi package) will be added. Because of the use of B splines the variables in homals will no longer be all factors, some can now be numerical ("continuous&quo...

Binary distributions of R-0.49 for NEXTSTEP (Intel and M68k) are now available on CRAN: http://www.ci.tuwien.ac.at/R/bin/i386-nextstep/R.0.49.I.b.tar.gz http://www.ci.tuwien.ac.at/R/bin/m68k-nextstep/R.0.49.N.b.tar.gz Because NEXTSTEP doesn't support dynamic loading, I've compiled in a number of additional functions (mostly from the user contributed section of CRAN) which I find

Hello I am looking for a function to create an Integrated (I) spline basis, somehting similar to the likes of 'bs' and 'ns'. I have come across the funcitons, fda::eval.monfd Values of a Monotone Functional Data Object fda::/.fd FDA internal functions fda::monfn Evaluates a monotone function fda::smooth.monotone Monotone

...rogrammed in C and/or FORTRAN (sometimes using existing routines), and the loop over variables will be parallelized using OpenMP or Grand Central Dispatch. For ordinal variables this requires some alternative quadratic programming routines to be linked in (which could then also become part of the isotone package). In addition the basic homals code will have object (individual) weights (minor addition) and the prehom routines (from the jacobi package) will be added. Because of the use of B splines the variables in homals will no longer be all factors, some can now be numerical ("continuous&quo...

I think that users quite often want to answers to questions like ``Is there something to do FOO in R?'', where FOO might e.g. be ``isotonic regression''. The answer should be something like ``you can use BAR in package BAZ, or ...''. For this, full text search is not the right approach and the keywords are not enough. We could maybe search dedicated fields (like \title),

Hi there, This is not a strictly related R question; I apologize for this. I'm interest in simulate the sampling distribution of the LRT, testing for trend among the levels of some categorical variable X in a regression model. (in practice this is achieved by assigning scores to the levels of X and fitting such numeric variable). To simulate the sampling distribution the steps are: 1.

Is there some reason why > (1:2)+(1:3) [1] 2 4 4 Warning message: In (1:2) + (1:3) : longer object length is not a multiple of shorter object length can't be made into an error? I realise it was there in S-PLUS, but since it produces a warning there can't be many examples on CRAN or Bioconductor using it, and I can't think of any situation where it would be used deliberately.

Hello, I am trying to call a FORTRAN subroutine from R. The Fortran code is @: http://lib.stat.cmu.edu/apstat/206 It performs a bivariate isotonic regression on a rectangular grid (m X n) matrix. I used the g77 compiler and successfully created a dll file and it also loads successfully from R. But somehow the programs fails to run properly. (I do get the correct result when I compile the

A colleague was asking me if R does multi-level modelling as opposed to multiple regression. Since I have no knowledge of multi-level modelling (except 5 minutes googling ) I thought that I would as here. Does are offer any multi-level modeling packages? It looked like arm might be one but I was not sure. Thanks