similar to: optmizing with monotone stepfunctions?

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

Hi, I am trying to use R to mimic what I did in SAS. proc transreg data=x ; model identity(GSI)=monotone(group1); output out=d2 pprefix=M; run; Accroding to SAS documentation, the MONOTONE transfomation algorithm comes from (Kruskal 1964, secondary approach to ties). I have tried ace. it does provide some kind of monotone transformation, but it is not what I expected. Here is how

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

Dear list, As can be seen below, adding a NA to the y values in a call to isoreg results in a segfault. ir4 <- isoreg(1:10, y4 <- c(5, 9, 1:2, 5:8, NA, 8)) Adding missing values to the x values, on the contrary, gives an error, but maybe the error message could be tailored to this particular situation. y <- c(5, 9, 1:2, 5:8, 3, 8) x <- c(1:9, NA) isoreg(x, y) ## error message:

Full_Name: Petr Klasterecky Version: 1.8.1 OS: Windows XP, Linux Submission from: (NULL) (195.113.27.212) The isoreg() function causes R to crash when called repeatedly. Consider the following simple script: { library(modreg) N <- 10 x <- rnorm(N) print("Original x values:") print(x) for(n in (1:N)){print(y <- isoreg(x[1:n])$yf)} } I am able to run (call) it several

Create the fixed-point intrinsics optimization celt_fir_neon() for ARM NEON. Create test tests/test_unit_optimization to unit test the optimization. --- .gitignore | 1 + Makefile.am | 39 ++++- celt/arm/arm_celt_map.c | 17 +++ celt/arm/celt_lpc_arm.h | 65 ++++++++ celt/arm/celt_lpc_neon_intr.c

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

Hello, If I want to see how, say, apply function is written, how would I be able to do that? Just typing "apply" at the prompt does not work. Thank you for help! Sergey

I believe there is a memory leak in isoreg in the current version of R, as I believe the following shows > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 120405 3.3 350000 9.4 350000 9.4 Vcells 78639 0.6 786432 6.0 392463 3.0 > for(k in 1:100) { + + y <- runif(10000) + isoreg(x,y) + } > rm(x) > rm(y) > gc() used (Mb) gc

Hi all, This is Linfeng Zhang from Google. I'll work on ARM NEON optimization in the next few months. I'm submitting 2 patches in the following couple of emails, which have the new created celt_fir_neon(). I revised celt_fir_c() to not pass in argument "mem" in Patch 1. If there are concerns to this change, please let me know. Many thanks to your comments. Linfeng Zhang

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"

Is there any reason to avoid looking at optimizing the encoding process? From just a simple profile run, it looks like a big chunk of the time is in seed_curve, sqrt, dradf4 and log. Are there big changes to the encoding part that are coming that would invalidate optimizations done now? -tim --- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project homepage:

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 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

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

Full_Name: Benjamin Tyner Version: 2.6.0 (43063) OS: WinXP Submission from: (NULL) (171.161.224.10) At the end of the examples for isoreg, there is cat("R^2 =", formatC(sum(residuals(ir4)^2) / (9*var(y4)), digits=2),"\n") I think this should be cat("R^2 =", formatC(1 - sum(residuals(ir4)^2) / (9*var(y4)), digits=2),"\n" Thanks Ben platform

Using > methods("plot") [1] plot.Date* plot.HoltWinters* plot.POSIXct* [4] plot.POSIXlt* plot.TukeyHSD plot.acf* [7] plot.data.frame* plot.decomposed.ts* plot.default [10] plot.dendrogram* plot.density plot.ecdf [13] plot.factor* plot.formula* plot.hclust* [16] plot.histogram* plot.isoreg* plot.lm [19] plot.medpolish*

Hi all, I'm sending patch "Optimize silk_warped_autocorrelation_FIX() for ARM NEON" in an separate email. It is based on Tim’s aarch64v8 branch https://git.xiph.org/?p=users/tterribe/opus.git;a=shortlog;h=refs/heads/aarch64v8 Thanks for your comments. Linfeng