similar to: Non-crossing Nonparametric quantile regressions

Dear R users, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())

Dear R users, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())

Hi All, What do you consider to be the best book(reference) on nonparametric regression? I am currently reading the book of Kunio Takezawa(2006): "Introduction to nonparametric regression". Is the book of Hardle(1990): "Applied nonparametric regression" better? or maybe another book? This is off topic, but most of the books is using R or S-plus. Thanks Hennie

Dear UseRs: Recently, I have read an article regarding the association between age and lymph node metastases. http://jco.ascopubs.org/content/27/18/2931.long In statistical analysis, the authors stated "Because a nonlinear relationship between age and lymph node involvement was expected based on existing literature, lymph node involvement was also regressed on age using nonparametric

Hi all, I'd like to compare species richness patterns of two groups with paired observations with an extra continuous fixed effect as a covariate. Normally I would use a standard general mixed effect model for such data, with one group variable and a continuous variable as fixed effects, plus a random effect for the paired observations. However, after making such a model with the lme

Hello! For comparing two non-normally distributed samples, Leech (2002) suggested to report nonparametric effect size indices, such as Vargha & Delaney's A or Cliff's d. I tried to search the R-sites, but could not find related procedures or packages that include nonparametric effect sizes. Thank you for your help! Citation: Leech (2002). A call for greater use of nonparametric

Sorry if this subject has been already dealt here. Which are some common tests for nonparametric k-way ANOVA? I have read about Kruskal-Wallis test as a kind of nonparametric one-way ANOVA, but I have not found anything about a general-setting (I mean k-way) nonparametric ANOVA. Can you recommend me a good R package (or other reliable software) for that? Looking forward to your answers, --

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

Dear all, Does anybody know how to get more evaluation points in performing Nonparametric analysis of repeated measurements data with "sm" library. The following command gives the estimation for 50 points, by I would like to increase to 100 points But I do not know how to do that. library(sm) provide.data(citrate, options=list(describe=FALSE)) provide.data(dogs,

Hi, I am doing my PhD and I usually use SPSS however now I need to do some multivariate nonparametric tests but SPSS don?t work with this. Recently I was aware of R and I saw that is possible using the MNM pack to perform multivariate nonparametric tests. I am learning step by step how to work in R meanwhile I need to perform the multivariate nonparametric tests for my PhD and I have no idea

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 --

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 all, Has any body the exprience to iclude a nonparametric component into the survival analysis using R package? *Can someone recommend *me * some ** references? * Thanks a lot Ashta [[alternative HTML version deleted]]

Dear All, I am using a specific approach for my master thesis. In essence, a supervised reclassification is used as an intermediate step to find chemical parameters which are able to reclassify defined groups. These variables will be used in a next step where location and scale estimators of the groups are important. Traditionally linear discriminant analysis is used for reclassification which

The new package "benchden" 1.0.0 implements 28 benchmark densities for nonparametric density estimation that were introduced by A. Berlinet and L. Devroye ("A Comparison of Kernel Density Estimates", Pub. Inst. Stat. Univ. Paris, XXXVIII, fasc. 3, 1994, 3-59, http://cg.scs.carleton.ca/~luc/devs.html ). This collection includes a variety of densities with different degrees of

The new package "benchden" 1.0.0 implements 28 benchmark densities for nonparametric density estimation that were introduced by A. Berlinet and L. Devroye ("A Comparison of Kernel Density Estimates", Pub. Inst. Stat. Univ. Paris, XXXVIII, fasc. 3, 1994, 3-59, http://cg.scs.carleton.ca/~luc/devs.html ). This collection includes a variety of densities with different degrees of

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

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

Dear All, I'm looking for?a way on computing the derivative of first and second order?of a smoothing curve produced by a nonprametric regression. For instance, if we run the R script below, a smooth nonparametric regression curve is produced. provide.data(trawl) Zone92?? <- (Year == 0 & Zone == 1) Position <- cbind(Longitude - 143, Latitude) dimnames(Position)[[2]][1] <-