similar to: new package benchden 1.0.0 : benchmark densities for nonparametric density estimation

Hi All, I've just rebuild the latest R with the Goto BLAS on our new Intel quad core machines. I did a few basic matrix calculations, and I was very impressed by the performance I saw. I wonder if anyone has a more rigorous benchmarking program for R. I downloaded a old R test/benchmarking program (see below), and this didn't work with the current R, and so I wondered if anyone could

Can anyone recommend a good nonparametric density approach for data bounded (say between 0 and 1)? For example, using the basic Gaussian density approach doesn't generate a very realistic shape (nor should it): > set.seed(1) > dat <- rbeta(100, 1, 2) > plot(density(dat)) (note the area outside of 0/1) The data I have may be bimodal or have other odd properties (e.g. point mass

Dear Sirs, My name is Marcelo Grimaldi and I work for GE Lighting Brazil in Six Sigma Program. In order to accomplish a statistical project I need to generate exact tables for the Kruskal-Wallis statistic ("Three or More Populations Location Test") and I wonder if R could help me. In the past I have heard of generating tables for Wilcoxon statistic using R. Could you help me ? Thank

Hi, I have seen a discussion in the R-help asking whether nonparametric manova has been implemented in R yet. This discussion is form March 2006 and there seemed to be no package or function implemented at the time. Has this changed? Is there a package that provides nonparametric manova as in McArdle and Anderson (2001) and Anderson (2001) now? Thanks, Daniel ------------------------- cuncta

Could somebody recommend some good nonparametric statistical inference textbooks for a beginner? And what are pros and cons of each book? Nonparametric statistical methods by Hollander seems to be more difficult for a beginner, but is great as a reference, right? Are there any books that are easier to learn than Hollander's? Also, I see some books in the wiki page. I don't find the

Dear useRs is there any nonparametric test for the analysis of variance in a design with two within-factors (repeated measures on both factors)? Friedman is not appropriate here, therefore I am grateful for any alternative test. thanks for any hint cheers christoph --

Hi! I'm doing one and two sample nonparametric tests for the median using wilcox test. For a one-sample test I use: > wilcox.test(x, mu =50 (or whatever), y=NULL,correct=TRUE) For two-sample test I use: > wilcox.test(x,y,correct=TRUE) The problem is when I try to duplicate problems from textbooks, I get p-values that are much different from the examples from the literature. They are

I've been looking for ways to calculate a large number (100) of non-crossing Nonparametric quantile regressions on large populations (1000+). Can the quantreg package in R ensure the non-crossing property? If not, do you know any alternative? Thank you, Paulbegc -- View this message in context:

Dear r-users, Any such a way that we can compute SPI using kernel function (nonparametric approach) without assuming any parametric distributions? Any existing package for above method using R? Thank you for your help. Fayyad [[alternative HTML version deleted]]

I am wondering if there is any package in R that can fit a nonparametric regression model with monotone constraints on the fitted results. --------------------------------- [[alternative HTML version deleted]]

Hi: I need to apply the IRT model from Ramsay (1991), He apply the Smoothing Kernel to multiple choice test. Is possible in R?. Thank you, Xavier G. Ordonez Doctoral Student Universidad Complutense de Madrid

Dear R users, Is it possible to apply 'predict' to an object of class "conmode"?  Could you please suggest me any applicable method for 'predict' for the "conmode" class? Thanking you, Sincerely Yours, Shyam Kumar Basnet SLU, Uppsala Sweden [[alternative HTML version deleted]]

Has anyone authored a Nonparametric approach to Canonical Correlation?

Hi All, Are there any package to check the GOF for nonparametric copulas using R? Fayyad [[alternative HTML version deleted]]

Dear friends. I hope you will bear over with a lengthy question. I have a problem of 76 patients on hemodialysis measured repeatedly once a month for nine months for methylmalonic acid and vitamin B12. The vitamin had been administered previously to these patients but was curtailed in the first part and then started again. There was a very clear response in that as vitamin B12 went down

For some small sample sizes I would like to exemplify the combinatorics underlying certain nonparametric tests like Mann-Whitney-Wilcoxon, Kruskal-Wallis and Spearman's rank correlation. I have written a function all.perm which delivers all permutations of 1,2,...,n and which works reasonably well. This can be used to generate P(R=r) of Spearman's rank correlation:

Dear all, Does R or S-plus or any of their packages provide Non-parametric "Run test" (which tests whether a sequence of numbers might be random or not)? If yes, i'd like a numerical illustration of this test. Any response / help / comment / suggestion will be greatly appreciated. Thanks in advance. ------------------------------- Mohammad Ehsanul Karim <wildscop at

Dear colleagues, has anyone an idea how to carry out a nonparametric manova for comparing 3 groups? Thank you for your help. Vera

Dear R Christoph Lehmann asked about this recently- as seen at http://finzi.psych.upenn.edu/R/Rhelp02a/archive/53191.html but the reply was not detailed. Did Christoph get a solution to this? Can anyone point me toward how to do repeated measures comparison using the the friedman test or other non-parametric test? I am trying to do something similar. Any example code would be useful.

Hello all, I'm a relatively new user of R, having mostly used it only for plotting so far. I'm also not very familiar with regression methods, hence forgive my greenness on the topic. What I want to do in R is multivariate nonparametric regression, with a slight hitch. From my experimental data I have a multitude of samples whose values approximate a function `f' that is defined